Identifying and presenting related electrical power distribution system events

ABSTRACT

Systems and methods to determine events that are associated with one another. Reports of a first, second, and third events are received. Based upon data associated with the first and second event, a determination is made that the first event is associated with the second event. Based upon data associated with the first event and the third event, a determination is made that the first event is not associated with the third event. A presentation is created indicating that the first and second events are related to the second event and that the first and third events are not related. The presentation is presented to a different process.

FIELD OF THE DISCLOSURE

The present disclosure generally relates to monitoring electrical powerdistribution system operations, and more particularly to identifying andpresenting information about related events.

BACKGROUND

Electrical power distribution systems generally include high voltageelectrical conductors that span a geographic area to distributeelectrical power to various customers in that geographic area. Theseelectrical power distribution systems also include various monitoringdevices and event reporting systems to report occurrences of variousevents that may affect the operation of the electrical distributionsystem. Reported events include, for example, indications of poweroutage in various portions of the electrical distribution system,occurrences of events, such as lightning, in the environment in an areaserved by the electrical distribution system, other events, orcombinations of these. In general, indications of these variousdifferent types of events are reported by different systems.

Some types of reported events include events that are likely to haveresulted from occurrences of excessive electrical current flow in theconductors of the electrical power distribution system. In someexamples, the excess electrical current is caused by a line fault in theelectrical conductors. Examples of such line faults include a shortcircuit or lower impedance path between two electrical phases at a pointin the electrical distribution system, or a short circuit or lowerimpedance path between a conductor and ground at a point in theelectrical distribution system.

In order to protect the electrical distribution system and maintainelectrical service to as many customers as possible in the event of aline fault, protection devices such as relays or other circuitinterruption devices operate when excessive electric current flow isdetected to disconnect the conductors in which the excessive electricalcurrent flow was detected. Some of the various monitoring devicesperform and report electrical current measurements when an excessiveelectrical current flow is detected. Different processing of thesereported electrical current measurements made by different monitoringdevices in some examples is able to provide different estimates of thelocation of a line fault that caused the excessive electrical currentflow. The estimated location of the line fault is generally specified asa probability that a line fault exists at a particular location on aconductor of the electrical distribution system. In general, thedifferent location estimates produced by the different processing ofdifferent measurements provide indicate that there is a substantialprobability that the line fault occurred over a relatively large portionof electrical conductors of the electrical distribution systems. Due tothe uncertainty of the location of the line fault, a physical inspectionby service personnel is generally performed over the entire relativelylarge portion of the electrical conductors to find the exact location ofthe line fault.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying figures where like reference numerals refer toidentical or functionally similar elements throughout the separateviews, and which together with the detailed description below areincorporated in and form part of the specification, serve to furtherillustrate various embodiments and to explain various principles andadvantages all in accordance with the present disclosure, in which:

FIG. 1 illustrates an electrical distribution system event processingsystem, according to an example;

FIG. 2 illustrates an associated event determination process, accordingto an example;

FIG. 3 illustrates a time and location associated event determinationprocess, according to an example;

FIG. 4 illustrates an example user interface, according to an example;

FIG. 5 illustrates an electrical distribution system and line faultlocation estimation table, according to an example;

FIG. 6 illustrates an information processing block diagram, according toan example;

FIG. 7 illustrates a composite fault map determination process,according to an example; and

FIG. 8 illustrates a block diagram illustrating a processor, accordingto an example.

DETAILED DESCRIPTION

As required, detailed embodiments are disclosed herein; however, it isto be understood that the disclosed embodiments are merely examples andthat the systems and methods described below can be embodied in variousforms. Therefore, specific structural and functional details disclosedherein are not to be interpreted as limiting, but merely as a basis forthe claims and as a representative basis for teaching one skilled in theart to variously employ the disclosed subject matter in virtually anyappropriately detailed structure and function. Further, the terms andphrases used herein are not intended to be limiting, but rather, toprovide an understandable description.

The terms “a” or “an”, as used herein, are defined as one or more thanone. The term plurality, as used herein, is defined as two or more thantwo. The term another, as used herein, is defined as at least a secondor more. The terms “including” and “having,” as used herein, are definedas comprising (i.e., open language). The term “coupled,” as used herein,is defined as “connected,” although not necessarily directly, and notnecessarily mechanically. The term “configured to” describes hardware,software or a combination of hardware and software that is adapted to,set up, arranged, built, composed, constructed, designed or that has anycombination of these characteristics to carry out a given function. Theterm “adapted to” describes hardware, software or a combination ofhardware and software that is capable of, able to accommodate, to make,or that is suitable to carry out a given function.

The below described systems and methods describe an automated process toreceive indications of various monitored events that may affect theoperation of an electrical power distribution system, identify eventsthat are associated with one another, and create a unified presentationof those associated events to clearly present relevant information tooperations personnel. These systems and methods in an example receiveevent reports indicating events that occur in an electrical distributionsystem, and identify associated events indicated by those event reportsbased upon various criteria. In an example, associated events are ableto be identified based upon one or both of a location associated withthe event or a time that the event occurred.

In some examples, events are able to be determined to be related withone another by one or more distances between locations associated witheach of those events. Such distances between events are able to bedistances along various paths between locations associated with theevents. In some examples, a distance between events is able to be astraight-line physical geographic path between the geographic locationsof the events. In other examples, a distance between two events isdefined as a distance along one or more electrical conductor lines of anelectrical distribution system that are connecting equipment reportingthe two events, which is sometimes referred to as a “schematicdistance.”

Schematic distances between two electrical distribution components insome examples are able to be further evaluated based upon thecharacteristics of the electrical conductor lines. For example,schematic distances between two components that are supplied electricalpower from different feeder lines may be determined to be greater thanschematic distances between two components that are supplied electricalpower from the same feeder line, even though the distance alongelectrical conductors between those two components is the same or lessthan distances along electrical conductors between components suppliedpower from different feeder lines.

In some examples, a schematic distance and a geographic distance betweentwo points can be different. In an example, two components of anelectrical distribution grid may have a short schematic distance but arelatively long geographic distance compared to differences betweengeographic distance and schematic distance that are observed betweenother points in the electrical distribution system. In another example,two such components are able to have a short geographic distance and along schematic distance. The below described systems and methods in someexamples are able to accurately and efficiently processes either or bothtypes of distances to determine, for example, whether events involvingtwo such components are associated with one another.

A geographic location associated with an event is able to be anyrelevant geographic location that pertains to the event. For example, inthe case of an event related to a loss of electrical power along alateral power distribution line, geographic locations associated withthat event may be a location of a device reporting the loss ofelectrical power on the lateral power distribution line, any locationthat has the loss of power as determined by any technique, a range ofgeographic locations that has the loss of power, geographic locations ofa loss of power determined by processing performed by devices thatmonitor and identify power line conditions that indicate a loss ofpower, other geographic locations pertinent to the loss of power, orcombinations of these.

Events are also able to be determined to be related based upon a timeinterval between occurrences of each event. In some examples, eventsthat occur within a determined time interval are determined to berelated, while events that are separated in time by more than thatinterval are determined to not be related to one another. Various timeintervals are able to be used based on various criteria. In an example,two or more events that may indicate an occurrence of a high electricalcurrent fault in the electrical distribution system may be determined tobe related if they occur within a relatively short time interval, suchas five (5) minutes. In other examples, events may be determined to berelated if they occur within relatively long time intervals, such as oneday, one week, or longer. In various examples, any time interval is ableto be used to determine whether events are related or not. In someexamples, an operator is able to specify a particular time interval andall events that occur within that specified time interval are determinedto be related and presented to the operator.

In an example, one event is able to be determined to be a selectedevent. Determination of a selected event is able to be based on anysuitable criteria. In various examples, a selected event is able to bebased on one or more of an operator selection of a previously reportedevent, one or more specified sets of criteria that allow automaticselection of a reported event satisfying those criteria as a selectedevent, other techniques may be used to determine a selected event, orany combination of these. In an example, other reported events areanalyzed relative to the selected event to determine which of the otherevents that are related to the selected event. For example, an operatoris able to select one reported event and characteristics of otherreported events are compared to that selected event to determine eventsthat are related to the selected event. In various examples, anycriteria is able to be used to determine events that are related to theselected event, such as one or more distances between each reportedevent and the selected event, time intervals between each reported eventand the selected event, any other criteria, or combinations of these.

In some examples, characteristics of some or all reported events areable to be analyzed to determine events that are related to one anotherwithout regard to a particular selected event. In such examples, aspecification of interrelationships between reported events is able tobe determined and maintained for some or all reported events.Determining interrelationships between some or all reported events isable to be performed as reports of events are received, based uponprocessing of stored data associated with event data that had beenpreviously received, or combinations of these.

Identifying events that are determined to be associated with one anotherallows excluding other events from further processing. In an example,processing of received indications of events is able to determine whichevents are associated with a particular event and create a presentationthat only includes indications of events that are determined to berelated to an that particular event. By including only events that arerelated to a particular event, unrelated events, which may be consideredas extraneous information or “noise” in evaluating and analyzing eventsthat affect the operations of an electrical distribution system, areable to be specially marked or excluded from further processing in someexamples. In some examples, unrelated events are able to be excludedfrom presentations of reported events, marked to allow for differentweighting in further analyses, handled in any suitable manner, orcombinations of these. Various actions are able to be taken based on theset of associated events that are produced by the below describedsystems and methods, such as more effectively and efficientlyidentifying problems with particular components of the electricaldistribution system, more quickly, effectively and efficientlydispatching service personnel to repair problems, other actions, orcombinations of these.

Determining events that are related to each other or to a selected eventassists in more effectively and efficiently analyzing patterns of eventsthat indicate problems in an electrical distribution system. In aparticular example of reported events indicating momentary power outagesin a utilities' electrical distribution system that serves over fourmillion (4 million) customers, more than twelve (12) event datareporting systems report approximately fifteen thousand (15,000)momentary power interruptions in a particular year. Manualidentification of reported events within the twelve (12) disparatereporting systems is very time consuming, manpower intensive, and errorprone process. Identification and repair of underlying problems with anelectrical power grid often requires analysis of reported events that atbest indirectly indicate underlying problems. In addition to reportedevents that reflect or otherwise provide information about a particularunderlying problem, the reported events include a large number ofunrelated and sometimes distracting reports that an operator mustmanually evaluate and assess with regards to the underlying problem thatpersonnel are trying to resolve and repair. Rapid restoration and repairof electrical distribution systems is often imperative due to thesometimes dangerous or life threatening conditions that can arise duringan electric power outage. A comprehensive determination of relatedevents from among the fifteen thousand (15,000) momentary powerinterruptions each year is often impractical in the relatively shorttime span in which underlying problems with an electrical distributionsystem must be addressed. Allowing personnel to quickly andautomatically identify related events in order to focus their analysison those related events is able to greatly reduce the time required toaddress underlying problems in a distribution system and improve theefficiency of the operations of an electrical system distribution systemby reducing the effort and time required to properly analyze, identify,mitigate, dispatch repair or service crews, otherwise address indicatedproblems, or combinations of these.

In some examples, many types of events, reports of events, or both, areable to be processed and analyzed to determine associated events. Insome examples, one or more systems or various types of equipment reportevents by sending one or more event reports by various techniques. Thevarious events or event reports are each able to have a particular typethat is one of a status event of a piece of equipment of the electricaldistribution system, an environmental event, a power distribution systemrelated event, any type, or combinations of these. In some examples, twoevents are able to be determined to be associated based, at least inpart, on the two events having different types, the two events havingthe same types, the two events having specified types, based on anycombination of types, or combinations of these.

In various examples, events are able to be reported via a number ofdifferent reporting systems that include monitoring equipment that ispart of the electrical distribution grid and also systems that are notconnected to the electrical distribution grid. For example, eventsassociated with electrical power delivery to customer premises are ableto be detected and reported by elements of a smart grid, or AdvancedMetering Infrastructure, system. Some electrical distribution systemcomponents are remotely monitored via Supervisory Control and DataAcquisition (SCADA) systems. Some electrical distribution systemsinclude monitoring equipment referred to as Fault Current Indicators(FCI) that automatically detect and estimate the location of electricalfaults within the electrical distribution system. Other devices, such asautomatic reclosers or Automatic Feeder Switches (AFS) detectovercurrent conditions and operate to open electrical circuits toprotect the electrical distribution system.

Reported events in some examples include events that are not directlyconnected with the electrical distribution systems. For example, weatherrelated events are able to be received from various sources and includedin the received events to determine if they are related to other events.In some examples, weather events include, but are not limited to, dataassociated with: lighting, wind measurements; occurrences, warnings, orboth, of tornados, hurricanes; data forecasting, observing, measuring,or otherwise associated with any one or more of rain, hail, flooding,ice, temperature extremes, earthquakes, or fires. Further, in someexamples, events that are analyzed to determined related events are ableto include reports of manmade events such as car or aircraft crashes,fire, or other manmade events.

Event reports from various reporting systems are able to be received byany suitable technique. For example, systems and components that arepart of a smart grid or Advanced Metering Infrastructure (AMI) systemare able to include a communications infrastructure to support efficientcommunications of event reports for detected events. Fault Currentindicators (FCIs) in some examples are able to wirelessly communicatevia a smart grid infrastructure or via any suitable communication systemor combination of systems. In some examples, Automatic Feeder Switches(AFS) communicate via a hardwired communications channel. SCADA systemsare able to communicate event reports over any suitable system, such asany combination of dedicated or shared communications systems that areable to include any combination of one or both of wired or wirelesscommunications links.

In one example, the systems and methods described herein are able toreceive event reports for various events, identify events that aredetermined to be associated with one another, exclude events that aredetermined to not be associated with one another, and support analysisof the associated events to more efficiently identify problems, resolveissues, perform other tasks, or combination of these. In an examplescenario of multiple events that may include events, a substation relayis tripped in close time proximity to a lightning strike that hits atree. The lighting strike causes the tree to fall and the tree shorts afeeder line coupled to and receiving power through the tripped relay,but the tree is located some miles away from the tripped relay. At aboutthat time as the lightning strike, one house that is geographicallyclose to the substation but receiving power through a different feederline experiences and reports a power outage while a neighboring housedoes not report a power outage.

In the above example, distant lightning strikes do not typically tripsubstation relays, but vegetation overgrowth is one of a multitude ofexpected possible causes for a relay being tripped. In this example,reports for all of these events and also a multitude of other events arereceived by the processing system. The tripped relay is a status eventof a piece of equipment of the electrical distribution system andreported via the utility's SCADA system. The power outage at the houseis an event reported via received the utility's AMI system, which isindependent of the SCADA system. While the reported power outage at thehouse occurred at about the same time as the reported relay trip and maybe geographically close to the tripped relay, the house is schematicallydistant from the tripped relay and the processing thus determines thatthe power outage at the house is not associated with the tripped relay.In this example, the observation that the house reporting the poweroutage has a neighboring house that still has power may validate thedetermination that report of the power outage at the house is notassociated with the tripped relay.

To continue with the above example, vegetation overgrowth was detectedover a week prior to the report of the relay tripping. The detectedvegetation overgrowth in this example corresponds to a powerdistribution system related event reported by one of several other eventreport systems and corresponds to a report filed by a manned crewvisually inspecting for vegetation overgrowth. Even though thevegetation event was reported over a week prior to the relay trip, it isconsidered close in time because of the nature of the event. Even thoughthe reported vegetation was some miles away from the tripped relay it isconsidered sufficiently close because schematically it has a distancethat is close to the switch. In this scenario, the lightning strike isan example of an environmental event reported by a lightning detectionservice, such as the National Weather Service, that is independent ofthe event reporting systems operated by the utility. While the distancebetween the lightning and the tripped relay is far, the lighting wasdetected close to the reported vegetation overgrowth, which wasdetermined to be associated with the tripped relay. In this example, thelighting strike is determined to be associated with the tripped relaydue to the proximity in time with the relay trip and its geographicallyclose distance to the vegetation. Consequently when analyzing thetripped relay, the information processor may facilitate quicklycommunicating a presentation to a service dispatcher to check thereported overgrowth vegetation which may have experienced a lightningstrike some distance from the relay, while ignoring the outage at thehouse close in time and geographically close to the relay because thepower outage at the house was determined not be associated with thetripped relay. Thus the process is able to analyze a large volume ofevent reports generated by disparate systems and processes are able tobe analyzed more quickly than humanly possible in order to effectivelyand efficiently associate related events and minimize the duration ofpower outages experienced by electric utility customers.

In some examples, associated events are able to include event reportsreceived from multiple systems that monitor the operation of electricaldistribution systems in order to estimate likely locations of detectedline faults in an electrical distribution system. Examples of linefaults include, but are not limited to, one conductor for one electricalphase having a short circuit or low impedance path to ground or to aconductor to another electrical phase. In some examples, these multiplesystems each determine an estimate of location of a line fault based onmeasurements made by different types of monitoring equipment and report.Each of these different monitoring and reporting systems in an exampledetermines a probability estimation of the location of a detected linefault at various positions along portions of the conductors of anelectrical distribution system. In an example, these multiple systemseach report events that include indications of a detected line fault aswell as their determined probability estimations at various positionsalong portions of the conductors of the electrical distribution system.

In an example, the below described systems and methods are able toinclude an automated process that receives event reports from variousmonitoring systems that each indicate detected line faults and that eachalso include location probabilities distributions along conductors ofthe electrical distribution system, determines that these multiplereports are associated with one another, and combines the locationsprobabilities in those multiple reports to determine a composite likelylocation probability of a detected line fault at various positions alongthe electrical power distribution system. In an example, an electricaldistribution system includes a number of processing systems that eachprovides a “fault map” that indicates probabilities along portions ofthe conductors of the electrical distribution system that indicateestimates of the location of detected line faults. Each of the systemsproviding the event reports in an example provides a fault map, eitheras part of the event report or as data available to the centralprocessing system, that specifies a respective location probabilitydistribution for a location of the detected line fault at each locationalong some conductors, or lines, in the electrical distribution system.Various fault maps in some examples are produced based upon measuredelectrical current surge measurements reported by different electricalcurrent monitoring devices. In an example, event reports that includefault maps provided by different monitoring systems are determined to beassociated based upon any suitable bases, such as one or more ofindicating faults that occurred at about the same time, indicatinglikely fault locations that overlap locations in the electricaldistribution systems, other criteria, or combinations of these.

In some examples, several ranges of probability values are defined andassigned an indicator for the probability of the location of a detectedfault at a particular location in the electrical distribution system.For example, probability values between eighty percent (80%) and onehundred percent (100%) are assigned the color “red” as an indicator. Insuch an example, probability values between sixty percent (60%) andeighty percent (80%) are assigned the color “yellow” as an indicator andprobability values below sixty percent (60%) are assigned the color“green” as an indicator. In such a system, a visual map of an electricaldistribution system is able to be presented with these three (3) colorssuperimposed at the respective locations corresponding to theprobability that the detected line fault occurred at that location. Sucha presentation is able to provide a ready indication of the likelylocation of a detected line fault.

Different estimated locations for a particular line fault are able to beproduced by the various systems used to estimate the locations ofdetected line faults. Various factors can lead to the different locationestimates produced by these different systems. For example, differentlocation estimation systems may receive electrical current measurementdata from different devices that are located at different locations ofthe electrical distribution system. These different measurement devicesmay also produce different types of electrical current measurement datathat support estimating line fault locations with different levels ofaccuracy. Due to many reasons, a particular line fault occurrence mayresult in the determination of a number fault maps that providedifferent probability values of a detected line fault occurring at eachlocation along a conductor.

In some examples, the below systems and methods operate to create acomposite fault map for a particular detected line fault. In an example,the composite fault map is based on a combination of fault maps for thatparticular detected line fault that were produced by various line faultlocation estimation systems. The composite fault map produced by thebelow described systems and methods is based on a composite locationprobability distribution that is produced by those systems and methodsand that provides a more refined estimated location of a detected linefault, and thus support reducing the area of the electrical distributionsystem that has to be physically inspected to find the actual locationof the line fault.

FIG. 1 illustrates an electrical distribution system event processingsystem 100, according to an example. The electrical distribution systemevent processing system 100 is an example of a system that performsvarious methods to receive indications of events, determine events thatare associated with one another, and produces sets of indications ofassociated events that have occurred.

The electrical distribution system event processing system 100 depictsan example electrical distribution system 160. The example electricaldistribution system 160 is a simplified illustration of some of thecomponents of electrical distribution systems that are used to supportthe operations of the below described systems and methods. Thissimplified illustration is used to provide a more clear and concisedescription of the relevant aspects of the below described systems andmethods. It is clear that the principles and techniques described hereinare applicable to any electrical distribution system or other similarsystems. As is described in further detail below, some components of theexample electrical distribution system 160 detect events and reportthose events to various information processors 140 via variouscomponents of a communications system 130.

The electrical distribution system 160 includes a substation 102 thathas a protection relay 108 and Supervisory Control and Data Acquisition(SCADA) equipment. As is generally understood, substation 102 in anexample receives electrical power from an electrical transmission ordistribution system (not shown) and provides electrical power todistribution system. In the simplified illustration, the substation 102provides electrical power through the protection relay 108, which in anexample is a feeder breaker. The electrical distribution system 160 inthis simplified example includes a first feeder line 110 that receivespower through the protection relay 108 and provides power to amonitoring device 1 104. The monitoring device 1 104 in this simplifiedexample is an Automatic Feeder Switch (AFS) that provides electricalpower to a second feeder line 112. In the illustrated example, thesecond feeder line 112 provides electrical power to a first lateral line113 and is also connected to a third feeder line 114 through amonitoring device 2 106, which in this example is a Fault CurrentIndicator (FCI). The illustrated example depicts that the third feederline 114 provides electrical power to a second lateral line 115 andcontinues on to provide electrical power to other elements (not shown).As is generally understood, substations in various distribution systemsare able to provide electrical power to any number of feeder lines,which in turn are able to be connected to and provide electrical powerto any number of lateral distribution lines.

In various examples, the monitoring device 1 104 and monitoring device 2106 in further examples are able to be any device that monitors eventsthat occur on the electrical distribution lines to which they areconnected. In some examples, such monitoring devices are part of, oroperate in association with, protection devices for the electricaldistribution system 160. Such protection devices are able to include,for example, any one or more of reclosers, Automatic Feeder Switches(AFSs), Automatic Lateral Switches (ALSs), any protection device, orcombinations of these. Further, monitoring devices are able to includeany type of monitoring device, such as Fault Current Indicators, variousSCADA monitoring and data acquisition equipment, any other type ofmonitoring device, or combinations of these. In some examples, suchmonitoring devices are able to be any device that monitors any type ofcondition associated with an electrical transmission line it ismonitoring. In some examples, monitoring devices do not monitorconditions on the electrical transmission lines but rather monitorconditions associated with all or part of the electrical distributionsystem 160. In some examples, the various monitoring devices sendreports of events that indicate their status, such as whether aprotection device has opened due to a detected over-current condition.An event report that indicates the status of such a device is an exampleof a status event of a piece of equipment in an electrical distributionsystem.

The electrical distribution system 160 includes smart meters group A 120connected to the first lateral line 113 and smart meters group B 122connected to the second lateral line 115. As is generally understood,each of these smart meter groups in an example contain a number of smartmeters that are each located at various customer facilities. Each smartmeter in each of these smart meter groups operate to measure electricalconsumption by those customer facilities and to also monitor andautomatically report various other conditions, such as loss ofelectrical power, voltage abnormalities, other events, or combinationsof these.

In the present description, the term “upstream” and “downstream” referto directions along electrical conductors relative to a point inelectrical distribution system 160. The term “upstream” refers to adirection along an electrical conductor that is towards a source ofelectrical power being carried by that electrical conductor. The term“downstream” refers to generally the opposite direction, which is adirection along the electrical conductor that is away from the source ofelectrical power being carried by that electrical conductor. Withreference to the electrical distribution system 160 described above,with regards to the monitoring device 2 106, the second feeder line 112is upstream of monitoring device 2 106, and the third feeder line 114 isdownstream of the monitoring device 2 106. Further, the monitoringdevice 1 104, the first feeder line 110, and the substation 102, withprotection relay 108, are all upstream of the monitoring device 2 106.In that example, the second feeder line 112, monitoring device 2 106,and the third feeder line 114 are all downstream of the monitoringdevice 1 104, while the first feeder line 110 and substation 102 withprotection relay 108 are upstream of the monitoring device 1 104.

The various monitoring devices, such as the above described substationSCADA equipment 124, protection relay 108, monitoring device 1 104,which is an Automatic Feeder Switch (AFS), monitoring device 2 106,which is a Fault Current Indicator, and smart meters group A 120 andsmart meters group B 122, communicate via various components of thecommunication system 130 and onto the information processors 140. In theillustrated example, smart meters group A 120 and smart meters group B122 communicate via Advanced Metering Infrastructure (AMI)communications elements 178. In particular, the substation SCADAequipment 124 and protection relay 108 communicate via a hard wiredsubstation communications link 164 to the communication system 130 andonto the information processors 140. Monitoring device 1 104, which isan AFS, and monitoring device 2 160, which is a Fault Current Indicator(FCI), communicates via a first AMI communications link 170 with the AMIcommunications elements 178 which are part of the communications system130 in this example, and onto the information processors 140. In theillustrated example, smart meters group A 120 and smart meter group B122 communicate via a second AMI communications link 172 with the AMIcommunications elements 178.

The electrical distribution system event processing system 100 furtherincludes environment sensors 132. In an example, a number of environmentsensors 132 are able to be located around the geographical area of theelectrical distribution system 160. In general, the environment sensors132 are able to detect and report occurrences of any type ofenvironmental event, such as any type of weather event or weatherrelated event. In an example, environment sensors 132 are able to detectoccurrences of lightning and report occurrences to a central processingsystem. A lightning strike detected by environment sensors 132 is anexample of an environmental event. Measurements of precipitation orother weather phenomena are also able to be sensed by suitableenvironment sensors 132. In some examples, environmental events are ableto be sensed, processed, and reported by various service providers thatare independent of a company operating the electrical distributionsystem 160, the information processors 140, or combinations of those.

The various event monitoring devices in the electrical distributionsystem 160 are able to report events to a processing system via any oneor more communications systems, subsystems components, or other elementsof the communications system 130. In various examples, the communicationsystem 130 is able to include one or more communications technologiesthat allow the various monitors to communicate data with remote devices.In various examples, the communications system 130 is able to includeany combination of one or more of wired communications circuits,wireless communications circuits, other communications circuits, or anycombination of these. In an example, the communications system 130 isable to include cellular data communications links, wired datacommunications links, Advanced Metering Infrastructure (AMI)communications elements 178, other elements or links, or any combinationof these. In general, the components or elements of communicationssystem 130 are able to be arranged, connected, interconnected, operatedin concert with or separately from each other according to any suitabledesign.

As illustrated for the electrical distribution system event processingsystem 100, equipment within substation 102, including protection relay108, monitoring device 1 104, monitoring device 2 106, the smart metersin both smart meter group A 120 and smart meter group B 122, and theenvironment sensors 132 all communicate via the communications system130. Although wireless communications links are shown in the illustratedexample, such communications lines are able to be implemented in variousexamples via, for example, any combinations of wired links, wirelesslinks, other links, or combinations of these.

The electrical distribution system event processing system 100 includesinformation processors 140. The information processors 140 in an exampleinclude various processors that perform various processing of data. Byway of example and without limitation, the information processors 140 invarious examples are able to include any combination of multipleprocesses execution within one or more physical processors, a number ofphysical processors that are able to be located at one or more physicallocations, any distribution of processing functions, or any combinationof these.

The communications system 130 in an example provides data received fromthe various monitors and other systems to information processors 140. Inan example, all reports of events received from any monitor associatedwith the electrical distribution system 160 are stored in an eventreport storage 146. In an example, the event report storage 146 storesevent histories for various events that occur within the electricaldistribution system, such as event histories of known electrical poweroutages that have occurred. In an example, processing performed by theinformation processors 140 accesses and processes previously receivedreports of events that are stored in the event report storage 146 inorder to determine events that are associated with each other.

In an example, a device location and grid schematic data storage 148stores geographical locations of all devices that report events to theinformation processors 140. In various examples, the device location andgrid schematic data storage 148 stores the geographical location, suchas in the form of latitude and longitude values, of each device that isable to report events. The device location and grid schematic datastorage 148 in some examples further stores descriptions of electricallines that interconnect each device to other devices in the electricaldistribution system. Such interconnection data supports integrating thetopology of electrical power interconnections of devices within theelectrical distribution grid into analyses of whether events are relatedto one another. In an example, the device location and grid schematicdata storage stores data describing the lengths of conductors connectingvarious reporting devices in order to support determining the distancealong conductors between two devices that report events.

A trouble ticket system 134 creates and manages service trouble ticketsused to support and manage operations and repairs of the electricaldistribution system 160. As is generally known, trouble tickets are ableto be created based upon various inputs, such as customer complaints ofa lack of electrical power or of electrical power serviceirregularities. The information processors 140 in an example receiveinformation regarding trouble tickets, such as listings of open troubletickets, trouble tickets that indicate occurrences of various events,other information within trouble tickets, or combinations of these. Theinformation processors 140 in an example determine events indicated byvarious trouble tickets and determines whether such events are relatedto other events reported by other sources to the information processors140. In some systems, the information processors 140 are able to includeprocessing to modify, create, or perform other actions with troubletickets maintained by the trouble ticket system 134. In an example,processing by the information processors 140 is able to determine eventsassociated with a trouble ticket maintained by the trouble ticket system134 and modify that trouble ticket to indicate that the event or eventsdetermined to be associated with the trouble ticket are the cause of theevent indicated by that trouble ticket.

A field observations reporting system 180 communicates informationregarding observations reported by, for example, field work crews orcustomers regarding various conditions related to electricaldistribution equipment. In an example, the field observations reportingsystem 180 includes reports received from work crews, other persons suchas customers, or other sources, regarding growth of vegetation such aspalm trees, bamboo shoots, vines, other growths, or combinations ofthese.

Other event reporting systems 136 includes other systems that reportevents associated with the operation, maintenance, other aspects, orcombinations of these, of the electrical distribution system 160. Theinformation processors 140 receive or access data associated with eventsreported by or available via the other event reporting systems 136. Thedata associated with events reported by or available via the other eventreporting systems 136 is processed by the information processors 140 inan example to determine which of those events are associated with eachother, are associated with other events reported by various systems, tosupport other processing, or combinations of these. Events reported bythe other event reporting systems are examples of power distributionsystem related events.

In some examples, related events are able to be determined from eventsand other data stored in any number of suitable systems. In variousexamples, data regarding events and other conditions is able to beobtained from one or more systems and presented to an operator foranalysis or other purposes. Manual review and evaluation of the largenumber of data items that are stored in each of a large number of eventstorage systems is often very time consuming and not practical whenworking under strict time constraints to restore electrical power orresolve other underlying problems in an electrical distribution system.Examples of systems from which data is able to be obtained include, butare not limited to:

1) Fault maps data from automated fault map generation systems thatestimate locations of detected line faults based on device readings, inan example this is an automatic process that is performed whenever suchevents occur.

2) Lightning or other environmental data organized by various timedurations, such as by each day, year, or by other durations, obtainedfrom various sources, including external weather data sources.

3) Lightning or other environmental data indicating lightning activitiesor other environmental data over a particular time duration, such asyear-to-date, obtained from various sources, including external weatherdata sources.

4) Information gathered in the field regarding vegetation conditions inthe field, which is able to be emailed in from users in the field andstored in a database.

5) Vegetation data that is able to be obtained from various sources suchas aerial photography, street/ground based photography, other sources,or combinations of these.

6) Open condition assessments from condition assessment data maintenancesystems with data obtained from, for example, users in the field thatnote conditions that need attention.

7) Customer complaint data is gathered through customer service systemsand stored in various databases. Such complaints are able to originatefrom actual logged customer complaints.

8) FCI (Fault Current Indicator) Fault data is retrieved from operationsrelated databases that contain, for example, recordings from the smartdevices in the field.

9) AFS (Automated Feeder Switch) Fault data is retrieved from operationsrelated databases that contain, for example, recordings from smartdevices in the field.

10) Trouble ticket data is sourced from the operations related troubleticket systems.

11) The open equipment log data is sourced from, for example, operationsrelated databases and represents equipment that is in need ofreplacement or repair.

12) Information regarding known momentary power outages or feederoutages is obtained from a various databases and based on actual feederoutage events; or any combination of these.

The condition assessment reports system 182 stores and provides reportsindicating condition assessments that are reported by various sourcesfrom the field, such as field inspection crews. Condition assessmentreports in an example are received and stored in the conditionassessment reports system 182 in order to support operations of anelectrical distribution system. In some examples, the informationprocessors 140 receive the condition assessment reports from thecondition assessment reports system 182 and process those reports todetermine events that the condition assessment reports may indicate. Theevents indicated by these received condition assessment reports are thenevaluated by the information processors 140 relative to other receivedevents in order to determine whether they are related to other reportedevents.

A failure prediction system 184 in an example provides estimations ofpredicted future times of failure for presently operating equipment. Insome examples, the failure prediction system 184 receives reports ofequipment operations, such as automatic recloser operations, protectionrelay operations, other operations, or combinations of these, andestimates when a particular piece of equipment is likely to fail. In anexample, the failure prediction system 184 tracks and analyzes the MeanTime Between Failure (MTBF) of various electrical distribution systemcomponents or system component health, such as by tracking amount ofhigh I²T exposure for a particular device. In such an example, thefailure prediction system 184 may generate a failure prediction systemreport that, for example, identifies a device that is statisticallyclose to failing and send that predication as an event to theinformation processors 140. The predicted failure of that device maythen be determined to be associated with other reported events and mayserve as an indication that failure of that device is a cause of theother reported events. An example of systems and methods that usevarious techniques to perform electrical power distribution gridmonitoring and failure prediction is described in U.S. patentapplication Ser. No. 15/002,180, filed Jan. 20, 2016, entitled “OutagePrevention in an Electric Power Distribution Grid using Smart MeterMessaging.” The entire contents and teaching of U.S. patent applicationSer. No. 15/002,180 is hereby incorporated herein by reference. In oneexample, in addition to determining associated events among reportedevent, further processing is able to evaluate reported events along withpredicted failures of one or more components of an electricaldistribution system in order to more completely provide an operator orother processor with a more complete set of information. In such anexample the component predicted to fail may be an underlying cause ofother events being reported by monitors within the electricaldistribution system.

An operator display 142 in an example presents presentations of datadepicting events that are determined to be associated with one another.In various examples, the operator display 142 is able to present listsof indications of events that are determined to be associated with eachother, present graphical presentations that indicate relativegeographical locations of events that are determined to be associatedwith one another, present any other type of display of relevantinformation to support analyses of multiple events that may beassociated with one another, or combinations of these. In some examples,the operator display 142 includes various user interface facilities thatpresent information to a user, receive inputs from a user, or both. Inan example, the operator display 142 includes user input facilities thatallows a user to specify a selection of a particular event to be used asa selected event. In an example, as is described in further detailbelow, other reported events that are related to that selected event aredetermined based on various processing. In an example, receiving aninput from a user, via the user input facilities of the operator display142, initiates processing to determine reported events that are relatedto the selected event specified by the received user's input.

A service dispatch component 144 in an example allows processing withinthe information processors to initiate service operations on theelectrical distribution system. In some examples, at least some of theoperations of a service dispatch component 144 are able to be performedvia the trouble ticket system 134. In other examples, the servicedispatch component is able to support different or additional exchangesof information with service personnel than are supported by the troubleticket system 134.

FIG. 2 illustrates an associated event determination process 200,according to an example. The associated event determination process 200is an example of a process that determines and identifies events areassociated with one another. In the illustrated example, the associatedevent determination process 200 depicts determining events that areassociated with an event of interest. The illustrated processing depictsdetermining events that are associated with one event of interest inorder to simplify the description of relevant aspects of thisprocessing. In further examples, similar processing is able to determineassociated events for any number of reported events, includingdetermining associated events for all events.

The following description of the associated event determination process200 refers to the components described above with regards to theelectrical distribution system event processing system 100. Theassociated event determination process 200 is an example of a processthat is performed on the information processor 140 based upon datareceived from multiple sources, such as by reporting devices sendingreports via the communication system, from other systems such as fromthe trouble ticket system 134, from other systems or sources, orcombinations of these.

The associated event determination process 200 begins by accumulatingevent reports from multiple sources, at 202. In various examples,reports indicating various events are received from various sourcesthrough the communication system 130 discussed above. These receivedreports in an example are stored in the event report storage 146. Invarious examples, accumulating event reports is able to includeretrieving event reports from the event reports stored in the eventreport storage, include processing event reports as they are receivedfrom various devices, any other receiving or retrieving of eventreports, or combinations of these. Additionally, indications of eventsin various examples are able to be received from any source.Accumulating event reports is an example of receiving a first eventreport indicating a first event, a second event report indicating asecond event that is different from the first event, and receiving athird event report indicating a third event that is different from thefirst event and the second event. In some examples, at least one of theevents indicated by an event report is able be at least one of a statusevent of a piece of equipment of the electrical distribution system, anenvironmental event; or a power distribution system related event.

An event of interest in one example is determined, at 204. Determiningan event of interest is able to be performed by any suitable technique.For example, an operator is able to select one event as an event ofinterest from among various events that are reported. Receiving aselection from an operator of an event and using that selected event asan event of interest is an example of receiving a selection of aselected event from within a plurality of events indicated by arespective plurality of event reports, and defining, based on theselection, the selected event as the first event.

In some examples, an event of interest is able to be determined basedupon a type of an event that was received. For example, a process may beconfigured to determine that certain types of reports are indications ofevents of interest. In an example, a report that a protection relayopened due to an over-current at a substation is able to be defined asan indication of an event of interest. When a report that a protectionrelay has opened, the associated event determination process 200responds by determining that the opening of the protection relay is anevent of interest.

The associated event determination process 200 continues by determining,at 206, events within the received event reports that are associatedwith the event of interest. Determining which events are associated withthe event of interest is able to be performed by any one or by anynumber of suitable techniques or criteria. In some examples, eventsassociated to the event of interest are determined by comparing datadescribing events that are described in received reports to datadescribing the event of interest.

The comparisons in various examples are able to be based on variouscriteria. In some examples, associated events are able to be defined asany event that occurred within a specified time period of the event ofinterest and that are also within a certain distance of the event ofinterest based on a geographic location associated with the event ofinterest and associated with the event being evaluated. In someexamples, events are determined to be associated with one another ifthey are within a certain distance along electrical distribution lines,i.e., schematic distances, that connect the devices that are reportingthe events. In some examples, events are able to be determined to beassociated with one another based upon combinations of relationships,such as proximity between the two events in one or more of either time,distance, or combinations of these. In an example, a first event andsecond event may be determined to be associated with one another basedon both time differences and distances between the two events both beingbelow respective thresholds. In that same example, the first event maybe determined to not be associated with a third event where the timedifferences between the first event and third event is below a timedifference threshold, but the distance between the first event and thirdevent is greater than a distance threshold.

In some examples, the associated event determination process 200 is ableto determine whether events are associated with one another, at 206,based on different criteria. In an example, events are determined to beassociated with one another if they are within a certain geographic areaand occur within one minute of each other. In another example, eventsare determined to be associated with one another if they are within acertain geographic area and occur within one hour or other specifiedtime interval of each other. In some examples, determining eventsassociated with an event of interest determines only events that occurwithin a specified time interval before the event of interest. In analternative example, determining events associated with an event ofinterest determines only events that occur within a specified timeinterval after the event of interest.

In some examples, a first event and a third event are able to bedetermined to be associated with one another based upon relationshipsbetween those two events and a second event that is separate from thosetwo. Such an association is able to be determined in an instance wherean analysis of the data associated with the first event and the thirdevent would indicate that the first event and the third event are notassociated with one another. In an example, a first event is associatedwith a third event based upon a determination of an association betweenthe first event and the second event, and further based upon adetermination of an association between the second event and the thirdevent.

Data in events reports for each of the determined associated events ispresented, at 208, while the presentation excludes data in events thatwere determined to not be associated. The presentation in variousexamples includes visual presentations, providing data to anotherprocess for further processing, assembling statistics, providing thedata to any data recipient process or display, any other type ofpresentation, or combinations of these. In some examples, data isgraphically presented in a manner that indicates a geographicalrelationship between and among the event of interest and the determinedassociated events. In an example this grouping allows a visual analysisof the interrelationships among the events that are determined to beassociated with the event of interest.

In an example, data about the reported events is updated, at 210. Invarious examples, further data about a particular event is able to bedetermined based upon characteristics of events that are determined tobe associated with that particular event. For example, multiple reportsof power outages, such as are reported by smart meters, that occurwithin a specified time interval of a report of a line fault on a feederline that is upstream of the smart meters reporting the power outageallows data concerning the reported power outages to be updated toindicate that the cause of the power outage is the reported upstreamline fault.

In another example, analysis of data within a report of an occurrence ofa lightning strike that occurs within a time interval before andgeographically near a reported power outage event supports an inferencethat the lightning strike likely caused the reported power outage. Insuch an example, a report of the power outage, such as a trouble ticketthat reported the power outage, is able to be updated to reflect thatthe lightning strike was the cause of the reported power outage.

In an example, a trouble ticket is able to be created or updated basedon the determined associations, at 212. In an example as described aboveof multiple reports of power outages that occur within a specified timeinterval of a report of a line fault on a feeder line that is upstreamof the smart meters reporting the power outage, a trouble ticket for theline fault is able to be created to repair the line fault. In anexample, trouble tickets created for the power outages reported by thesmart meters are able to be updated to indicate that the line fault isthe cause of those power outages and repair of the line fault is likelyto resolve those trouble tickets.

In an example, feedback is received, at 214, on the determinedassociations. In some examples, feedback is able to be received invarious forms. In some examples, an operator is able to provide feedbackthat specifies whether an event that was determined to be associatedwith the event of interest is not really associated, or whether an eventthat was determined to not be associated should have been determined tobe associated with the event of interest. In another example, a user ofthe presented data is able to, for example, associate some events asbeing more closely related to the event of interest. In some examples,an operator is able to identify that the event of interest was at leasta partial cause of another reported event. For example, an event ofinterest may be a detected lightning strike, and associated events maybe loss of electrical power in the geographical area of the lightningstrike. In such an example, an operator may judge that the lightningstrike is at least partially a cause for the nearby loss of electricalpower.

Based upon this received feedback in some examples, criteria fordetermining associated events are updated, at 216. For example, criteriasuch as the maximum geographical distance between two associated eventsis able to be adjusted based on the geographic distance between twoevents that received feedback indicates are associated with each other.Similarly, the maximum time differences between events that are to bedetermined to be associated with one another are able to be adjustedbased on time differences between events that feedback indicates areassociated with one another.

In an example, the associated event determination process 200 returns toaccumulating event report from multiple sources, at 202. The abovedescribed processing is then re-iterated. In various examples,iterations of the associated event determination process 200 are able tobe executed where different events of interest are able to bedetermined, such as being selected by an operator, and events associatedwith those different events of interest are then identified.

FIG. 3 illustrates a time and location associated event determinationprocess 300, according to an example. The time and location associatedevent determination process 300 is an example of a process performed aspart of the above described associated event determination process 200.With reference to the above description, the time and locationassociated event determination process 300 is an example of processingincluded in determining related events within event reports that areassociated with events of interest 206.

The time and location associated event determination process 300determines, at 302, a time associated with the event of interest. Asdescribed above, the event of interest is able to be determined by anysuitable technique. In some examples, the event of interest is specifiedby an operator or by another automated process controlling the operationof processes that determine associated events. In various examples, areport of an event that is determined to be the event of interestspecifies a time associated with the event. In some examples, this timeis a time at which the event occurred. In further examples, this time isa time during which the event occurred, a time at which the eventstopped, any other time associated with the event of interest, orcombinations of these. In some examples, a time of an event of interestis able to specify a time span over which the event of interestoccurred, a time span over which the event of interest affectedoperations of any system, other time spans, or combinations of these.

A time span for related events is determined, at 304. The time span forassociated events in an example is the time span over which to searchfor events that may be associated with the event of interest. In someexamples, a determined time span is able to be one minute, one hour, oneday, another interval of time, or any combination of these. In anexample, events occurring outside this time span are determined to benot associated with the event of interest. In some examples, the timespan is determined based upon a specification by an operator of the timespan of interest around the determined event of interest that maycontain events of interest. In some examples, this time span is able tobe based upon the type of event that is determined to be an event ofinterest. For example, time spans for events associated with an event ofinterest such as a lightning strike may be one minute, while time spansfor events associated with an event of interest such as a particulartrouble ticket that indicates a facility does not have power may belonger, such as ten (10) minutes, one hour, other intervals, orcombinations of these. In some examples, the time span is able to be atime interval of the determined duration that occurs before the abovedetermined time associated with the event of interest, a time intervalof the determined duration that occurs after the above determined timeassociated with the event of interest, a time interval that spans bothbefore and after the above determined time associated with the event ofinterest, a time interval that has any temporal relationship to theabove determined time associated with the event of interest, or anycombination of these.

Events that occur within the determined time span (e.g., a thresholdtime difference) of the event of interest are identified, at 306. In anexample, such events are identified by examining received reports ofevents and identifying each event that occurred within the determinedtime span. In some examples, times associated with events are specifiedor otherwise indicated within the received reports for various events.

A region of interest around a location associated with the event ofinterest is determined, at 308. The size of a region of interest aroundlocations associated with an event of interest (e.g., a thresholddistance) is able to be determined based on any criteria. In someexamples, the region of interest is specified as a geographic areaaround the event of interest. In some examples, that geographic area isable to have its boundaries specified by any suitable technique, such asby the latitude and longitude values of those boundaries. In someexamples, the region of interest is specified according to distancesalong electrical distribution lines, i.e., schematic distances, thatconnect to the device reporting the event of interest by less than aspecified length.

In an example, associated events are determined, at 310, where theassociated events are eventssecond feeder that are within the determinedtime span and within the region of interest are determined, at 310. Insome examples, events are determined to be associated or not associatedbased on proximities of the events to one another, where the proximityis able to be one or more of a time difference, schematic distance, ageographic distance, or combinations of these. In an example,determining associated events consists of processing each report ofevents that are received from all reporting systems and excluding eventsthat occurred outside of the determined time span (e.g., a thresholdtime difference) and outside of the determined geographic area. In someexamples, events that are within the determined geographic area aredetermined based upon identifying a location within the electricaldistribution system of the device that reported the event of interest,and then identifying reports of candidate events that are received fromdevices connected along electrical distribution lines to the device thatreported the event of interest by less than a specified distance (e.g.,a threshold distance). In various examples, the specified distance isable to be specified by any suitable technique, which may include anumber and/or type of intervening devices or grid elements, or thelength of the conductors of the electrical distribution system thatconnect the device reporting the candidate event to the device reportingthe event of interest. Distances along conductors connecting devices inthe electrical distribution system are referred to herein as distancesaccording to the electrical power line routings. In an example, theseconductors are also able to connect with other devices that also reportevents. In an example, events that are reported by devices that are ineither direction along the conductors of the electrical distributionsystems, i.e., devices that are either upstream or downstream of thedevice reporting the event of interest, are considered. In furtherexamples, devices that are only upstream, or only downstream, of thedevice reporting the event of interest are considered. In variousexamples, the determined geographic area is a maximum length ofconductors connecting devices reporting candidate events to the devicereporting the event of interest, the determined geographic area is ageographical boundary specified by, for example, latitude and longitudevalues, the determined geographic is any suitable geographic boundary,or the determined geographic boundary is able to be any combination ofthese.

The data of the associated events is then presented, at 312. Thispresentation is an example of the presenting data event reports, at 208,as described above. This presentation is able to include any actionconveying any data associated with the determined associated events,including visual presentation, electronic communication of any dataassociated with determined associated events to another process ordevice, any other communications of any data associated with determinedevents, or any combination of these. The time and location associatedevent determination process 300 then ends.

FIG. 4 illustrates an example user interface 400, according to anexample. The example user interface 400 illustrates portions of asimplified electrical distribution system and reported events that havebeen determined to be associated with one another. The example userinterface 400 depicts associated reported events and components of theportion of the electrical distribution system that are within thegeographic bounds at the edges of the example user interface 400. Theexample user interface 400 is an example of a display presented to, forexample, a user on a workstation such as the above described operatordisplay 142. The example user interface in an example is produced by theabove described information processor 140 based on various reportedevents that are obtained from any of a variety of sources. The exampleuser interface 400 depicts a subset of those reported events that havebeen filtered based on various criteria to determine which events arerelated to one another. As described above, such filtering is able to bebased on a time frame of when the events occurred, distances between theevents, other criteria, or combination of these.

The example user interface 400 depicts a simplified electricaldistribution network that includes a substation 402, various portions orsegments of a single feeder line that receives electrical power from thesubstation, and several lateral lines that are connected to and thatreceive power from that feeder line. In further examples, a similar userinterface is able to present all of the relevant elements of theelectrical distribution system being monitored or analyzed, which ofteninclude multiple feeder lines and many lateral lines.

The example user interface 400 includes indications of likelihoods thata detected fault condition is located at various portions of thedepicted feeder line and lateral lines. In an example, the detectedfault may be a reason why an operator would choose to view relatedevents. In an example, a particular event within all reported events,such as the operation of an Automatic Feeder Switch (“AFS”) thatindicates a line fault, is able to be selected by an operator and allevents related to that selected event are depicted on the userinterface. In general, analysis of occurrences and causes of anycondition, such as any type of line fault, any type of distributionsystem abnormality, other condition, or combinations of these, is ableto be facilitated by use of a user interface similar to the depictedexample user interface 400.

The substation 402 in this example provides electrical power to a firstfeeder line segment 404. The first feeder line segment 404 has a firstfault current indicator 460. A Fault Current Indicator (FCI) 460monitors the electrical current that flows through that device andprocesses data measured during detected overcurrent events to estimate alocation of an electrical fault that may have caused the detectedovercurrent event. The first feeder line segment 404 further has a firsttrouble ticket indication 420, which reads “NLS” to indicate it is a “NoLoss of Service” trouble ticket. A first “Automatic Feeder Switch”(“AFS”) or “IntelliRupter” (“IR”) 450 is depicted as connecting thefirst feeder line segment 404 to a second feeder line segment 406.

In this example, automated processing of overcurrent events processesdata contained in event reports that was collected in association withdetected faults to estimate the location of that detected fault.Estimated fault location data in some examples provide probabilityvalues that indicate, at various points along conductors of anelectrical distribution system, whether the detected fault had occurredat that particular point. The example user interface 400 depicts, as isdescribed in further detail below, a composite fault map for the portionof the electrical distribution system that it depicts. In an example,the depicted composite fault map indicates a respective composite linefault likelihood value for each displayed point or line segment. In theexample user interface 400, displayed portions of the electricaldistribution system include single crosshatched portions to indicatesegments with a medium likelihood of being the location of a detectedline fault. The example user interface 400 also includes doublecrosshatched portions to indicate segments with a high likelihood ofbeing the location of a detected line fault. Areas without crosshatchingindicate segments with a low likelihood of being the location of adetected line fault.

In various examples, as is also described in further detail below, suchportions of the fault maps, including composite fault maps, of anelectrical distribution system are able to be depicted with differentcolors, such as portions of distribution lines in red indicating anextremely high likelihood of a fault, portions in orange indicating avery high likelihood of a fault, portions in yellow indicating mediumhigh likelihood of a fault, and lines with a low likelihood of being alocation of a fault being depicted in different colors. In someexamples, different portions of distribution lines that are determinedto have a low likelihood of being a location of a detected fault aredepicted in various different colors to allow a viewer to easilyvisualize and distinguish different lines, such as different feeder linesegments or lateral lines, according to the geographical layout anddesign and of the particular electrical distribution system. In anexample, the portions of the distribution lines

The second feeder line segment 406 depicted in the example userinterface 400 is depicted as having a single cross hatch pattern and isshow to be connected to, and thus able to provide electrical current to,a first lateral line 412 and a second lateral line 410. The firstlateral line 412 is also depicted with a single crosshatch to indicatethat there is a medium likelihood that a detected fault is located onthe first lateral line 412. The first lateral line 412 further includesa second AFS 462.

A portion of the second lateral line 410 is depicted with a singlecrosshatch to also indicate that there is a medium likelihood that adetected fault is located on the second lateral line 410. A secondtrouble ticket 430, which reads “LAT” to indicate it is a “lateral”trouble ticket, is depicted near the junction of the second feeder linesegment 406 and the second lateral line 410. The second lateral line 410also includes a first condition assessment 440, which indicates that aninspection of the second lateral line 410 produced an assessed conditionseverity of “2.”

A third feeder line segment 407 is depicted with a double crosshatch toindicate that there is a high likelihood that a detected fault occurredin this portion of the feeder line. The third feeder line segment 407further includes a second AFS or “IntelliRupter” 452, which operates ina manner similar to that of a recloser. The third feeder line segment407 in this example extends to a junction of a third lateral line 414,where the feeder line continues as a fourth feeder line segment 408.

The fourth feeder line segment 408 is depicted with a single crosshatchto indicate a medium likelihood that a detected fault has occurred inthis segment of the feeder line. A third lateral line 414 is depicted ashaving no crosshatching, thus indicating that there is a low likelihoodof the detected fault having occurred in the third lateral line 414.

In the illustrated example user interface 400, a depiction of acomposite fault map that shows medium or high likelihood that a linefault occurred in the second feeder line segment 406, the first lateralline 412, the second lateral line 410, the third feeder line segment407, and the fourth line feeder segment. These segments are depicted inthis example with crosshatching indicating either a medium or highlikelihood that a detected fault has occurred those segments. In someexamples, the other depicted segments that are not shown withcrosshatching are also part of a composite fault map but are depicted toindicate a low, but not necessarily zero, probability that a detectedline fault has occurred in those segments.

A third trouble ticket 432 near the intersection of the third lateralline 414 and the feeder line. The third trouble ticket 432 reads “TX,”which indicates it is a transformer trouble ticket. The third lateralline 414 also has a fourth trouble ticket 470 which reads “SV,”indicating that it is a “Service” ticket, and an fifth trouble ticket422 which reads “NLS” indicating it is a “No Loss of Service” troubleticket.

A fifth feeder line segment 409 is depicted without crosshatching toindicate a low likelihood that that the detected fault occurred in thissegment of the feeder line. The fifth feeder line segment 409 includes afifth trouble ticket 424 that reads “NLS” to indicate it is a “No Lossof Service” trouble ticket, and also has a sixth trouble ticket 472 thatreads “SV” indicating it is a “Service” ticket. A fourth lateral line418 is connected to, and thus received electrical power from, the fifthfeeder line segment 409. The fourth lateral line 418 has a secondcondition assessment 442, which indicates a severity of “3,” and a thirdcondition assessment 444, which indicates a severity of “4.”

FIG. 5 illustrates an electrical distribution system and line faultlocation estimation table 500, according to an example. The electricaldistribution system and line fault location estimation table 500 depictsa simplified electrical distribution system 502 and a line faultlocation estimation table 504. The present description uses a simplifiedelectrical distribution system 502 is similar to the above describedexample electrical distribution system 160 and includes components tohelp more clearly and concisely describe the relevant aspects of thebelow described examples associated with creating composite fault mapsbased on a number of event reports that each provide estimated locationsof fault locations along electrical conductors of an electricaldistribution system. Some components of the simplified electricaldistribution system 502 correspond to similar components of the exampleelectrical distribution system 160 described above. It is clear that theprinciples and concepts described below can be readily applied toelectrical distribution systems of any complexity.

The simplified electrical distribution system 502 depicts a substation510 and an electrical distribution line 506 with a number of monitorsdistributed along that electrical distribution line 506. In an example,the substation 510 is able to be similar to the above describedsubstation 102. The illustrated electrical distribution line 506 is anexample of an electrical line that has a number of electrical currentmonitors along its length. In general, a substation 510 receiveselectrical power from an electrical transmission system (not shown) andin turn provides electrical power to a number of feeder lines fordistribution over a geographic area. These feeder lines in general eachprovide electrical power to a number of lateral lines that are connectedto various points on the feeder line in order to further distributeelectrical power over that geographical area. It is to be understoodthat the principles described below with regards to the electricaldistribution line 506 are able to be easily and directly applied to anelectrical distribution system that includes a number of substationsthat each provide power to a number of parallel feeder lines and whereeach feeder line provides power to a number of lateral lines connectedto various points along those feeder lines.

The illustrated electrical distribution line 506 includes a number ofmonitors distributed along its path. These monitors, as are describedbelow, in general contain electrical current monitors that performvarious measurements of the electrical power conveyed along theelectrical distribution line 506 and communicate those measurements viaa communication system 570. In various examples, the communicationsystem 570 is able to include one or more communications technologiesthat allow the various monitors to communicate data with remote devices.In various examples, the communications system 570 is able to includeany combination of one or more of wired communications circuits,wireless communications circuits, other communications circuits, or anycombination of these. In an example, the communications system 570 isable to include cellular data communications links, wired datacommunications links, Advanced Metering Infrastructure (AMI)communications elements, other elements or links, or any combination ofthese. The communications system 570 in some examples is similar to orhas components similar to those included in the communications systems130 described above.

The communications system 570 in an example provides data received fromthe various monitors and other systems to an information processingcomponent 572. As is described in further detail below, the informationprocessing component 572 includes various processors that performvarious processing of data. In an example, the information processingcomponent 572 is able to receive data reported via the communicationssystem 570 to estimate locations of detected lines faults. In anexample, the information processing component 572 includes a compositefault map processor that is able create a composite fault map as isdescribed below. In an example, the information processing component 572is similar to or part of the above described information processors 140.The information processing component 572 is then able to, in an example,coordinate service operations with a service dispatch component 574 todispatch service personnel to inspect locations that are determined tobe likely locations of a detected line fault in order to locate andrepair the detected line fault. In an example, the service dispatchcomponent is similar to or part of the above described service dispatchcomponent 144.

The substation 510 in this example has a protection relay 511 thatconnects the substation 510 to a first end of segment 1 520 of theelectrical distribution line 506. The protection relay 511 in thisexample operates with an electrical current detector 509 that performsmeasurements of the electrical current provided to segment 1 520 and theother segments connected to segment 1 520. The electrical currentdetector 509 is able to, for example, detect an incidence of excessiveelectrical current being drawn by a load connected to the substationthrough the segment 1 520. An occurrence of an excessive amount ofelectrical current flowing through a conductor, which is generallydefined as an amount of electrical current that exceeds a threshold, isreferred to herein as an “over-current condition.” Such an over-currentcondition is able to be associated with a line fault on the electricalcircuit being provided with electrical power via segment 1 520. Theelectrical current detector 509 in an example records measurements ofthe electrical current surge associated with an over-current conditionand commands the protection relay 511 to open and disconnect electricalpower from segment 1 520 when an over-current condition is detected.

In some examples, electrical current detector 509 is able to includefurther processing or measurement equipment to produce various types ofdata to characterize the electrical current during an over-currentcondition. Examples of these different data that are able to be producedby the electrical current detector 509 include, but are not limited to,a detailed description of the electrical current peak transient duringthe over-current condition, alternating current (AC) electrical currentphase shifts relative to the AC voltage waveform during the over-currentcondition, other measurements, or combinations of these. Such varioustypes of data in some examples are able to support different line faultlocation estimation processing that may have different accuracies,reliability, other characteristics, or combinations of these.

The illustrated electrical distribution line 506 is a simplifieddepiction of an electrical line that includes a feeder line section 590and a lateral line section 592. As is understood by practitioners ofordinary skill in the relevant arts, a substation 510 is able to provideelectrical power to number of feeder lines, and each feeder line is ableto provide electrical power to a number of lateral lines that areconnected at various locations along the feeder line. The illustratedelectrical distribution line 506 is presented with this simplifiedstructure in order to more concisely and clearly present the belowdescribed processing.

The illustrated feeder line section 590 includes segment 1 520, segment2 522, segment 3 524 and segment 4 526. A monitor A 512 in this exampleconnects segment 2 522 to segment 3 524. The illustrated lateral line592 includes segment 5 580, segment 6 582 and segment 7 594. In thisexample, monitor B 514 connects segment 4 526 of the feeder line section590 to segment 5 580 of the lateral line 592. Monitor C 516 connectssegment 6 582 to segment 7 584 of the lateral line 592. Each segment inthis context is a portion of an electrical line that is located at aparticular location on the electrical line. In some examples, line faultlocation estimation processing assigns to each segment a likelihood, orprobability, that a detected line fault occurred in that particularsegment.

In the following discussion, segments, monitors, or other devices in anelectrical line are referred to as being beyond or after one another, oras being before, preceding, or ahead of one another. These terms ingeneral refer to the relative locations of an element to another elementin a relative to the power source providing power to the electoral line.For example, with reference to the electrical distribution line 506,because of their relative locations to the substation 510 providingpower to the electrical distribution line 506, monitor B 514 is referredto as being beyond or after monitor A 512, and preceding or ahead ofmonitor C 516.

The electrical distribution line 506 includes a number of monitors thatperform electrical current measurements to support line fault locationestimation. In the illustrated example, the electrical current detector509 performs measurements that support location estimation of detectedline faults anywhere on the electrical distribution line 506. Monitor A512 performs measurements that support location estimation of detectedline faults that occur beyond monitor A 512, such as within segment 3524, segment 4, 526, segment 5 580, segment 6 582 or segment 7 584.Monitor B 514 performs measurements that support location estimation ofdetected line faults that occur beyond monitor B 514, such as withinsegment 5 580, segment 6 582 or segment 7 584. Monitor C 516 performsmeasurements that support location estimation of detected line faultsthat occur beyond monitor C 516, which includes segment 7 584 in thisexample. The electrical current detector 509, monitor A 512, monitor B514, and monitor C 516 in the illustrated electrical distribution line506 are examples of electrical current meters.

Electrical current monitors, such as are included in the electricalcurrent detector 509, monitor A 512, monitor B 514, and monitor C 516,are able to include any electrical monitoring device that producesmeasurements of electrical current flow and reports such measurementsvia the communication system 570. In various examples, electricalcurrent monitors are able to include various circuits that producevarious measurements of electric current. In some examples, electricalcurrent monitors are able to produce and report various types ofmeasurements that support different processes to estimate locations ofdetected line faults. In some examples, without limitation, electricalcurrent monitors are able to produce a detailed description of theelectrical current peak transient during the over-current condition,alternating current (AC) electrical current phase shifts relative to theAC voltage waveform during the over-current condition, othermeasurements, or combinations of these.

In various examples, electrical current monitors are able to be anysuitable device that is able to measure and report electrical currentflowing through the device. By way of example and not limitation,monitors such as monitor A 512, monitor B 514, monitor C 516, othermonitors, or combinations of these, are each able to include one or moreof an Automatic Feeder Switch (AFS), an Automatic Lateral Switch (ALS),a Fault Current Indicator (FCI), other devices, or combinations ofthese.

The line fault location estimation table 504 depicts data contained infault maps determined by a number of processing techniques along with acomposite fault map that is based on a combination of those other faultmaps. The line fault location estimation table 504 presents likelihood,or probability, values for each segment that indicates the likelihoodthat a detected line fault is located in that particular segment. Inthis illustrated example, ranges of likelihood values are indicted bycolor. Probabilities, or likelihood values, for locations of detectedline faults are presented in this example due to inaccuracies inestimating line fault locations based on electrical currentmeasurements. Due to such inaccuracies and unknowns, using a color topresent a range of values provides more useful data when evaluating thelocation estimates of a line fault.

In the line fault location estimation table 504, the color “green” isindicated by a letter “G,” the color “yellow” is indicated by a letter“Y,” and the color “red” is indicated by a letter “R.” In this example,a color “red” indicated by an “R” for a particular segment indicatesthat the line fault is more likely to be located in that segment. Acolor “yellow” indicated by a “Y” for a particular segment indicatesthat the line fault is less likely to be located in that segment. Acolor “green” indicated by a “G” for a particular segment indicates theline fault is unlikely to be located in that segment. In an example,these colors are able to indicate probability ranges as is describedabove.

The line fault location estimation table 504 includes a monitorreporting column 560 and a segment field 562 that has a number ofcolumns each labeled with a segment number. The line fault locationestimation table 504 has a number of rows with one row for each monitordescribed above for the simplified electrical distribution system 502,and a composite row 530 that depicts composite likelihood values foreach segment in the segment field 562. The line fault locationestimation table 504 further has a number of columns that includeindications of a likelihood that a line fault occurred in a particularline segment. The line fault location estimation table 504 includes asegment 1 column 532 that has an indication for each row that indicatesa likelihood value that a line fault is located in segment 1 520.Similarly, indications of likelihood values of a line fault beinglocated in other segments of the feeder line section 590 are in asegment 2 column 534 that has indications of a likelihood value that aline fault is located in segment 2 522, a segment 3 column 536 that hasindications of a likelihood value that a line fault is located insegment 3 524, and a segment 4 column 538 that has indications of alikelihood value that a line fault is located in segment 4 526.Likelihood values for line faults in the lateral line 592 are shown in asegment 5 column 540 that has indications of a likelihood value that aline fault is located in segment 5 580, a segment 6 column 542 which hasindications of a likelihood value that a line fault is located insegment 6 582, and a segment 7 column 544 has indications of alikelihood value that a line fault is located in segment 3 524. In eachcolumn, the likelihood value in each row is based upon a value of alocation probability distribution estimating that a line fault'slocation is in the segment associated with that column, where thelocation probability distribution is determined based measurements madeby the electrical current monitor associated with that row.

A current detector row 550 has “current detector” in the monitorreporting column 560 and indications of likelihood values that adetected line fault occurred in each segment, as determined based onmeasurements reported by the electrical current detector 509, are listedin the columns of the segment field 562. A monitor A row 552 has“monitor A” in the monitor reporting column 560 and indications oflikelihood values that a detected line fault occurred in each segmentare listed in the columns of the segment field 562. The likelihoodvalues that a detected line fault occurred in each segment aredetermined in an example by processing measurements received frommonitor A 512. A monitor B row 554 and monitor C row 556 have “monitorB” and “monitor C” in the monitor reporting column 560, respectively,and also have indications of likelihood values that a detected linefault occurred in each segment in the columns of the segment field 562as are determined by processing measurements received from monitor B 514and monitor C 516, respectively.

The likelihood values in the illustrated line fault location estimationtable 504 are based on an example of a line fault to ground havingoccurred in segment 6 582 of the electrical distribution line 506described above. Because a line fault to ground occurred in segment 6582, a surge current associated the line fault flows from the substationthrough the electrical current detector 509, monitor A 512, and monitorB 514. Because there is a line fault to ground in segment 6 582, theelectrical current surge associated with the line fault does not reachmonitor C 516 and thus no measurement data indicating a line fault isreported by monitor C 516.

The current detector row 550 presents line fault likelihood values foreach segment following the electrical current detector 509. In anexample, surge electrical current measurements made by the electricalcurrent detector 509 are reported to the information processing segmentvia the communications system. The electrical current measurementsreported by the electrical current detector 509 are processed in anexample to determine a fault map that indicates a likelihood value thata detected line fault occurs in a particular segment of the electricaldistribution line 506. Because all of the electrical current supplied tothe electrical distribution line 506 in this example flows through theelectrical current detector 509, the current detector row 550 is able toprovide likelihood of a line fault having occurred in each segment ofthe electrical distribution line 506. Although likelihood values areable to be determined for each segment, a number of uncertainties mayresult in less accuracies being associated with the determinedlikelihood values for more remote segments. The current detector row 550indicates “green” in segment 1 column 532, “yellow” in each of segment 2column 534 through the segment 4 column 538, and “red” in the segment 5column 540 through the segment 7 column 544.

The monitor A row 552 presents line fault likelihood values for eachsegment following the monitor A 512. In an example, surge electricalcurrent measurements made by the current monitor A 512 are reported tothe information processing segment via the communications system andprocessed in an example to determine a fault map that indicates alikelihood value that a detected line fault occurs in a particularsegment of the electrical distribution line 506. Because monitor A 512is located between segment 2 522 and segment 3 524, the monitor A row552 is able to provide likelihood of a line fault having occurred insegments that received power through monitor A 512, such as segment 3524 and the segments following it. The monitor A row 552 in this exampleindicates “green” for segment 3 524 and segment 4 526, and “yellow” foreach of segment 5 580 through segment 7 584.

Monitor B row 554 presents line fault likelihood values for each segmentfollowing the monitor B 514 in manner similar to that described abovewith regards to monitor row A 552 and monitor A 512. Because monitor B514 is located between segment 6 582 and segment 7 584, the monitor Brow 554 is able to provide likelihood of a line fault having occurred insegments that received power through monitor B 514, which are segment 5580, segment 6 582 and segment 7 584. The monitor B row 554 in thisexample indicates “yellow” for segment 5 580 and “red” for both segment6 582 and segment 7 584.

Monitor C row 556 presents determined line fault likelihood values foreach segment following monitor C 516. In this example, as mentionedabove, a line fault to ground occurred in segment 6 582 so no line faultrelated current surge would flow through monitor C 516 because it islocated downstream of segment 6 582 at the connection between segment 6582 and segment 7 584. Because no line fault related current surge ismeasured by monitor C 516, no data is available to process to determinea likelihood that a line fault occurred in a segment receivingelectrical power through monitor C 516. Thus, the monitor C row 556 inthis example contains no data.

The composite row 530 depicts a composite fault map that containscomposite likelihood values for each segment. The values in thecomposite row 530 are determined in an example by an algorithm thatprocesses data contained in two or more fault maps, such as the faultmap data presented in the current detector row 550, monitor A row 552,monitor B row 554, monitor C row 556, or combinations of those.

The composite fault map presented in the composite row 530 in thisexample is a combination of likelihood values contained in all of thefault maps that were determined based upon measurements made by at leastone monitor. In the illustrated example, the value in each column of thecomposite row 530 is a weighted average that is calculated for all ofthe values in that column of the segment field 562. For example, thesegment 1 column 532 and the segment 2 column 534 indicate “green,”which reflects the value in the current detector row 550 of thosecolumns, which is the only row of those columns with a value.

The segment 3 column 536 and the segment 4 column 538 both indicate“yellow” for the composite row 530, which in this example is a weightedaverage of the likelihood values in the current detector row 550 andmonitor A row 552. The segment 5 column 540 indicates “yellow” for thecomposite row 530, which in this example is a weighted average of thelikelihood values in the rows of that column. The segment 6 column 542and the segment 7 column 544 both indicate “red” for the composite row530, which in this example is a weighted average of the likelihoodvalues in the other rows of that column.

In further examples, other algorithms are able to determine thecomposite likelihood values for the composite fault map. Examples ofother processing and algorithms are described in further detail below.

FIG. 6 illustrates an information processing block diagram 600,according to an example. With references to the electrical distributionsystem and line fault location estimation table 500 discussed above, theinformation processing block diagram 600 depicts a block diagram ofcomponents in the information processing component 572, discussed above,along with the communications system 570 and service dispatch component574 discussed above.

The information processing component 572 includes a communicationsinterface 610 that, in an example, receives data reported via thecommunications system 570 by various monitors in the electricaldistribution line 506. The communications interface 610 in an exampleprovides the received data to one or both of a first fault locationestimation process 612 and a second fault location estimation process614. The depicted example includes two fault location estimationprocesses in order to more concisely and clearly describe the relevantaspects of the described examples. In various examples, any number offault location estimation processes that implement various types ofprocessing are able to be included in an information processingcomponent 572.

In the illustrated example, the first fault location estimation process612 and the second fault location estimation process 614 produce faultmaps that indicate probability values of the location of a detected linefault. The first fault location estimation process 612 produces a firstset of fault maps 616 and the second fault location estimation process614 produces a second set of fault maps 618. In an example, the firstfault location estimation process 612 processes data determined by andreceived from the electrical current detector 509 that operates with theprotection relay 511 discussed above to produce a fault map for eachline fault detected based upon information from the electrical currentdetector 509. In an example, the second fault location estimationprocess 614 processes data produced by and received from other monitorslocated along feeder lines and lateral lines in order to produce faultmaps indicating estimates of locations of detected line faults. In someexamples, a separate fault map is generated based upon data produced byand received from each individual monitoring device along feeder lines,such as the illustrated feeder line section 590, and lateral lines, suchas the illustrated lateral line 592. Fault maps may also be generatedbased upon the systems and sensors including those described withrespect to FIG. 1.

The information processing component 572 further includes a compositelocation estimation determination process 620. The composite locationestimation determination process 620 is an example of a processperformed by a composite fault map processor. In an example, thecomposite location estimation determination process 620 receives faultmaps from one or more sources, such as from either one or both of theillustrated first set of fault maps 616 and the second set of fault maps618, and produces a composite location estimation for each determinedline fault. An example of a process performed by the composite locationestimation process to produce a composite location estimation from anumber of fault maps is described in further detail below.

The composite location estimation determination process 620 producesinformation to present line fault locations estimates on a locationestimation display 630. In an example, the location estimation display630 is able to present a display similar to the above described exampleuser interface 400, which presents the data defining a composite faultmap. The composite location estimation determination process 620 in someexamples also provides estimated line fault locations to a servicedispatch interface 632. The service dispatch interface 632 in an exampleis then able to provide the estimated line fault location to the servicedispatch component 574 to allow the service dispatch system to, forexample, more efficiently direct physical inspection of feeder lines orlateral lines to determine the location of the line fault and performneeded repairs.

FIG. 7 illustrates a composite fault map determination process 700,according to an example. The composite fault map determination process700 is provided by way of illustration and not limitation as an exampleof a process performed by the above described composite locationestimation determination process 620.

The composite fault map determination process 700 receives, at 702,fault maps based on measurements from multiple monitoring devices. Withreference to the information processing component 572 described above,the composite fault map determination process 700 receives fault mapsfrom the first set of fault maps 616 and the second set of fault maps618. In general, the composite fault map determination process 700 hasaccess to a number of fault maps for line faults that occurred atvarious times and at very locations.

The composite fault map determination process 700 assembles, at 704,likely line fault location data for line faults that occur within aspecified time interval. In general, measurements associated with a linefault are made very shortly after the line fault occurs. Informationabout a particular line fault will generally be based upon measurementsthat are made at approximately the same time. The composite fault mapdetermination process 700 assembles line fault location data for oneparticular line fault in order to have more likely assembled line faultlocation data that is associated with the same line fault.

The composite fault map determination process 700 determines, at 706, acomposite line fault likelihood value for each segment. In an example, acomposite fault map is generated that indicates a respective compositeline fault likelihood value for each line segment being monitored. In anexample, the respective composite line fault likelihood value for aparticular line segment is determined based on a mathematicalcombination of a number of likelihood values that a line fault islocated in that particular line segment as are indicated in a number ofvarious fault maps. These various fault maps in an example aredetermined based upon measurements produced by one monitor or a subsetof monitors that monitor the power distribution lines providingelectrical power to a line that has a line fault.

In an example, determining a composite line fault likelihood value for aparticular segment includes computing a weighted average of thelikelihood values for that particular segment contained in two morefault maps. For example, a likelihood values in a fault map from thesecond set of fault maps 618 may be given more weight than likelihoodvalues in a fault map from the first set of fault maps 616.

In another example, determining a composite line fault likelihood valuefor a particular segment is based on selecting the fault map that isdetermined based on measurements made by an electrical current monitorthat is the farthest from a power source providing power to theelectrical line containing substation and reporting the line fault. Itis assumed in some examples that the electrical current monitor that isfarthest from the power source is also closest to the line fault. In anexample, determining the composite line fault likelihood value for aparticular segment includes using the line fault likelihood value forthat segment that was determined for that segment in the fault map thatwas created using data from the electrical current monitor that isfarthest from the substation providing power to the electrical linesince that electrical current monitor is likely to be closest to theline fault.

In another example, determining a composite fault likelihood value for aparticular segment is based on selecting the fault map that isdetermined based on measurements made by an electrical current monitorthat is closest to and before, or upstream of, an electrical currentmonitor that did not report measurements related to an overcurrentcondition. In an example, a line fault prevents electrical energy fromflowing past that fault, and electrical current monitors beyond the linefault will not experience excessive electrical current during the linefault. It is then assumed in some examples that the closest electricalcurrent monitor to a line fault, and thus the electrical current monitorthat produces the most relevant electrical current measurements relatedto that electrical line fault, is the electrical current monitor thatreports electrical current measurements indicting a line fault that isclosest to and before another electrical current monitor that did notreport current measurements indicating a line fault. In such an example,determining the composite line fault likelihood value for a particularsegment includes using the line fault likelihood value for that segmentthat was determined for that segment in the fault map that was createdusing data from the electrical current monitor that is closest to andbefore an electrical current monitor that did not report electricalcurrent measurements indicating a line fault.

A composite line fault likelihood value for at least some line segmentsis presented, at 708. In an example, such a presentation includes acomposite fault map that indicates composite line fault likelihoodvalues for at least some line segments being monitored. In an example,presenting a composite line fault likelihood value for at least someline segments includes presenting a display similar to the abovedescribed example user interface 400, which presents the data defining acomposite fault map.

In some examples, a service crew is dispatched, at 710, to a likelyfield location of the line fault based on the composite line faultlikelihood value for a line segment at the likely field location.Dispatching a service crew to a likely field location of the line faultin this context is an example of directing a service inspection to apartition location to inspect the electrical line, where the particularlocation is based on a composite location probability distribution.Dispatching a service crew to a likely field location with one or moresegments that have higher line fault likelihood values based oncombining the fault likelihood values for those segments from a numberof different fault maps in an example reduces the geographic area ofline segments that have to be inspected to find the line fault.

In some examples, a determined location of the line fault is received,at 712. In an example, the determined location is reported by theservice crew that is dispatched to find and repair the line fault. Infurther examples, the determined location is able to be received fromany source or determined by any technique.

One or more algorithms that is used to calculate the composite linefault likelihood value for each line segment is then updated, at 714. Inan example, the algorithm is updated based on a correspondence betweenthe determined location of the line fault, such as is received at 712,and probabilities within the at least two of the location probabilitydistributions indicted by at least two fault maps. Updating thesealgorithms in this way is able to improve the accuracy of locationsestimates for line faults made in the future. Updating these algorithmsby using the actual determined locations of line faults whose locationswere estimated by the above processing will allow improving the accuracyof the algorithm. In an example, updating an algorithm that combineslikelihood values from multiple fault maps may include changing weightvalues given to likelihood values from each of the models in order toproduce more accurate location estimations. The composite fault mapdetermination process 700 then returns to receiving, at 702, fault mapsand follows with the processing described above.

FIG. 8 illustrates a block diagram illustrating a processor 800according to an example. The processor 800 is an example of a processingsubsystem that is able to perform any of the above described processingoperations, control operations, other operations, or combinations ofthese.

The processor 800 in this example includes a CPU 804 that iscommunicatively connected to a main memory 806 (e.g., volatile memory),a non-volatile memory 812 to support processing operations. The CPU isfurther communicatively coupled to a network adapter hardware 816 tosupport input and output communications with external computing systemssuch as through the illustrated network 830.

The processor 800 further includes a data input/output (I/O) processor814 that is able to be adapted to communicate with any type ofequipment, such as the illustrated system components 828. The datainput/output (I/O) processor in various examples is able to beconfigured to support any type of data communications connectionsincluding present day analog and/or digital techniques or via a futurecommunications mechanism. A system bus 818 interconnects these systemcomponents.

Information Processing System

The present subject matter can be realized in hardware, software, or acombination of hardware and software. A system can be realized in acentralized fashion in one computer system, or in a distributed fashionwhere different elements are spread across several interconnectedcomputer systems. Any kind of computer system—or other apparatus adaptedfor carrying out the methods described herein—is suitable. A typicalcombination of hardware and software could be a general purpose computersystem with a computer program that, when being loaded and executed,controls the computer system such that it carries out the methodsdescribed herein.

The present subject matter can also be embedded in a computer programproduct, which comprises all the features enabling the implementation ofthe methods described herein, and which—when loaded in a computersystem—is able to carry out these methods. Computer program in thepresent context means any expression, in any language, code or notation,of a set of instructions intended to cause a system having aninformation processing capability to perform a particular functioneither directly or after either or both of the following a) conversionto another language, code or, notation; and b) reproduction in adifferent material form.

Each computer system may include, inter alia, one or more computers andat least a computer readable medium allowing a computer to read data,instructions, messages or message packets, and other computer readableinformation from the computer readable medium. The computer readablemedium may include computer readable storage medium embodyingnon-volatile memory, such as read-only memory (ROM), flash memory, diskdrive memory, CD-ROM, and other permanent storage. Additionally, acomputer medium may include volatile storage such as RAM, buffers, cachememory, and network circuits. Furthermore, the computer readable mediummay comprise computer readable information in a transitory state mediumsuch as a network link and/or a network interface, including a wirednetwork or a wireless network, that allow a computer to read suchcomputer readable information. In general, the computer readable mediumembodies a computer program product as a computer readable storagemedium that embodies computer readable program code with instructions tocontrol a machine to perform the above described methods and realize theabove described systems.

In an example, the disclosed methods include a method for combining linefault location probabilities. The method in an example includesreceiving a first location probability distribution for a location of anline fault along an electrical line based upon at least a firstelectrical current measurements reported by a first electrical currentmonitor at a first location along the electrical line, and receiving asecond location probability distribution of the location of the linefault along the electrical line based upon at least a second electricalcurrent measurements reported by a second electrical current monitor ata second location along the electrical line, the second electricalcurrent measurements being made within a time interval of the firstelectrical current measurements. The method further includes determininga composite location probability distribution for the location of theline fault along the electrical line based on an algorithm processingthe first location probability distribution and the second locationprobability distribution, and providing the composite locationprobability distribution.

In some further examples of these methods, the determining the compositelocation probability distribution is based on combining likelihoodvalues according to an algorithm, the method further includes receivinga determined location of the line fault along the electrical line, andupdating the algorithm based on a correspondence between the determinedlocation and probabilities within the first location probabilitydistribution and the second location probability distribution.

Other examples of these methods further include directing a serviceinspection to a particular location to inspect the electrical line, theparticular location being based upon the composite location probabilitydistribution.

In some examples, the electrical line receives power from a power sourceand the second electrical current monitor is electrically farther fromthe power source than the first electrical current monitor. In theseexamples, the determining the composite location probabilitydistribution includes selecting the second location probabilitydistribution as the composite location probability distribution basedupon the second electrical current monitor being farther from the powersource than the first electrical current monitor.

In some further examples, the electrical line receives power from apower source and the second electrical current monitor is electricallyfarther from the power source than the first electrical current monitor.In these examples, a third electrical current monitor is electricallyfarther from the power source than the first electrical current monitorand the second electrical current monitor and w the second electricalcurrent monitor is upstream from and electrically closest to the thirdelectrical current monitor. Further the third electrical current monitordoes not report measurements indicating the line fault, and thedetermining the composite location probability distribution includesselecting the second location probability distribution as the compositelocation probability distribution based upon the second electricalcurrent monitor being electrically closest to and upstream from thethird electrical current monitor.

In some examples, the electrical line includes a plurality of linesegments, the first location probability distribution includes arespective first likelihood value for each line segment in the pluralityof line segments, and the second location probability distributionincludes a respective second likelihood value for each line segment inthe plurality of line segments. In these examples the determining thecomposite location probability distribution includes determining arespective composite likelihood value for each line segment based upon acombination of the respective first likelihood value and the respectivesecond likelihood value for each line segment in the plurality of linesegments. In some of these examples, each respective first likelihoodvalue has a respective first color value and each respective secondlikelihood value has a respective second color value, and the respectivecomposite likelihood value has a respective composite color value foreach line segment where the respective composite color value for arespective particular line segment is determined based on a mapping ofthe respective first color value and the respective second color valuefor the respective particular line segment.

In an example, composite fault map processor includes a processor and amemory communicatively coupled to the processor where the processor,when operating, is configured to receive a first location probabilitydistribution for a location of an line fault along an electrical linebased upon at least a first electrical current measurements reported bya first electrical current monitor at a first location along theelectrical line, and receive a second location probability distributionof the location of the line fault along the electrical line based uponat least a second electrical current measurements reported by a secondelectrical current monitor at a second location along the electricalline, the second electrical current measurements being made within atime interval of the first electrical current measurements. Theprocessor is further configured to determine a composite locationprobability distribution for the location of the line fault along theelectrical line based on an algorithm processing the first locationprobability distribution and the second location probabilitydistribution, and provide the composite location probabilitydistribution.

In some examples the processor is configured to determine the compositelocation probability distribution based on combining likelihood valuesaccording to an algorithm, and is further configured, when operating, toreceive a determined location of the line fault along the electricalline, and update the algorithm based on a correspondence between thedetermined location and probabilities within the first locationprobability distribution and the second location probabilitydistribution.

In some examples, the processor is further configured, when operating,to direct a service inspection to a particular location to inspect theelectrical line, the particular location being based upon the compositelocation probability distribution.

In some examples of the composite fault map processor, the electricalline receives power from a power source, and the second electricalcurrent monitor is electrically farther from the power source than thefirst electrical current monitor. The processor is also configured todetermine the composite location probability distribution by at leastselecting the second location probability distribution as the compositelocation probability distribution based upon the second electricalcurrent monitor being farther from the power source than the firstelectrical current monitor.

In some examples of the composite fault map processor, the electricalline receives power from a power source, and the second electricalcurrent monitor is electrically farther from the power source than thefirst electrical current monitor. In these examples, a third electricalcurrent monitor is electrically farther from the power source than thefirst electrical current monitor and the second electrical currentmonitor and wherein the second electrical current monitor is upstreamfrom and electrically closest to the third electrical current monitor,and the third electrical current monitor does not report measurementsindicating the line fault. In these examples the processor is configuredto determine the composite location probability distribution by at leastselecting the second location probability distribution as the compositelocation probability distribution based upon the second electricalcurrent monitor being electrically closest to and upstream from thethird electrical current monitor.

In some examples of the composite fault map processor, the electricalline includes a plurality of line segments, the first locationprobability distribution includes a respective first likelihood valuefor each line segment in the plurality of line segments, and the secondlocation probability distribution includes a respective secondlikelihood value for each line segment in the plurality of linesegments. The processor in these examples is configured to determine thecomposite location probability distribution by at least determining arespective composite likelihood value for each line segment based upon acombination of the respective first likelihood value and the respectivesecond likelihood value for each line segment in the plurality of linesegments.

In some examples of the composite fault map processor, each respectivefirst likelihood value includes a respective first color value and eachrespective second likelihood value includes a respective second colorvalue, and the respective composite likelihood value has a respectivecomposite color value for each line segment where the respectivecomposite color value for a respective particular line segment isdetermined based on a mapping of the respective first color value andthe respective second color value for the respective particular linesegment.

In an example, a computer program product for determining a compositefault map includes a computer readable storage medium having computerreadable program code embodied therewith, where the computer readableprogram code includes instructions for: receiving a first locationprobability distribution for a location of an line fault along anelectrical line based upon at least a first electrical currentmeasurements reported by a first electrical current monitor at a firstlocation along the electrical line, and receiving a second locationprobability distribution of the location of the line fault along theelectrical line based upon at least a second electrical currentmeasurements reported by a second electrical current monitor at a secondlocation along the electrical line, the second electrical currentmeasurements being made within a time interval of the first electricalcurrent measurements. The computer readable program code furtherincludes instructions for determining a composite location probabilitydistribution for the location of the line fault along the electricalline based on an algorithm processing the first location probabilitydistribution and the second location probability distribution, andproviding the composite location probability distribution.

In some examples of the computer program product, the instruction fordetermining the composite location probability distribution determinethe composite location probability distribution based on combininglikelihood values according to an algorithm In these examples, thecomputer readable program code further includes instructions forreceiving a determined location of the line fault along the electricalline, and updating the algorithm based on a correspondence between thedetermined location and probabilities within the first locationprobability distribution and the second location probabilitydistribution.

In some examples of the computer program product, the computer readableprogram code further includes instructions for directing a serviceinspection to a particular location to inspect the electrical line, theparticular location being based upon the composite location probabilitydistribution.

In some examples of the computer program product, the electrical linereceives power from a power source and the second electrical currentmonitor is electrically farther from the power source than the firstelectrical current monitor. In these examples, the instructions fordetermining the composite location probability distribution includeinstructions for selecting the second location probability distributionas the composite location probability distribution based upon the secondelectrical current monitor being farther from the power source than thefirst electrical current monitor.

In some examples, the computer program product, the electrical linereceives power from a power source, and the second electrical currentmonitor is electrically farther from the power source than the firstelectrical current monitor. In these examples, a third electricalcurrent monitor is electrically farther from the power source than thefirst electrical current monitor and the second electrical currentmonitor, the second electrical current monitor is upstream from andelectrically closest to the third electrical current monitor, and thethird electrical current monitor does not report measurements indicatingthe line fault. In these examples the instructions for determining thecomposite location probability distribution include instructions forselecting the second location probability distribution as the compositelocation probability distribution based upon the second electricalcurrent monitor being electrically closest to and upstream from thethird electrical current monitor.

In some examples of the computer program product, the electrical lineincludes a plurality of line segments, the first location probabilitydistribution includes a respective first likelihood value for each linesegment in the plurality of line segments, and the second locationprobability distribution includes a respective second likelihood valuefor each line segment in the plurality of line segments. In theseexamples, the instructions for determining the composite locationprobability distribution include instructions for determining arespective composite likelihood value for each line segment based upon acombination of the respective first likelihood value and the respectivesecond likelihood value for each line segment in the plurality of linesegments.

In an example, the disclosed methods include a method for determiningevents that are associated with one another. The method in an exampleincludes receiving a first event report indicating a first eventassociated with an electrical distribution system, receiving a secondevent report indicating a second event different from the first event,the second event being associated with the electrical distributionsystem, receiving a third event report indicating a third eventdifferent from the first event and the second event, the third eventbeing associated with the electrical distribution system, determining,based upon data associated with the first event and the second event,that the first event is associated with the second event, and alsodetermining, based upon data associated with the first event and thethird event, that the first event is not associated with the thirdevent. The method further includes creating a presentation indicatingthat the first event is related to the second event and that the firstevent is not related to the third event, and providing the presentationto a different process.

In further examples, methods are also able to include the above methodwherein at least one of the first event report, the second event report,or the third event report includes a report indicating at least one of astatus event of a piece of equipment of the electrical distributionsystem, an environmental event, or a power distribution system relatedevent. In some examples, at least one of the first event report, thesecond event report, or the third event report includes a failureprediction system report.

In further examples, methods are also able to include the above methodand further include receiving, a selection of a selected event fromwithin a plurality of events indicated by a respective plurality ofevent reports, and defining, based on the selection, the selected eventas the first event. In some examples, the selection is received via auser interface.

In further examples, methods are also able to include the above methodswherein the determining the first event is associated with the secondevent is based upon a first proximity of the first event to the secondevent, and wherein the determining the first event is not associatedwith the third event is based upon a second proximity of the first eventto third event. Additionally, in some examples the first event occurs ata first time, the second event occurs at a second time, and the thirdevent occurs at a third time, wherein the first proximity is based upona first time difference between the first time and the second time,wherein the second proximity is based upon a second time differencebetween the first time and the third time, wherein the determining thefirst event is associated with the second event is based upon the firsttime difference being below a threshold, and wherein the determining thefirst event is not associated with the third event is based upon thesecond time difference being above the threshold. In some examples, thefirst event report is sent by a first device, the second event report issent by a second device different from the first device, and the thirdevent report is sent by a third device separate from the first deviceand the second device, and wherein the first proximity is based upon afirst distance between the first device and the second device, whereinthe second proximity is based upon a second distance between the firstdevice and the third device, wherein the determining the first event isassociated with the second event is based upon the first distance beingbelow a threshold, and wherein the determining the first event is notassociated with the third event is based upon the second distance beingabove the threshold. Further, the first distance and the second distanceare each a respective distance according to one or both of electricalpower line routings or respective geographic locations associated witheach respective event in the first event, the second event and the thirdevent.

In an example, a processor is disclosed that includes a processor and amemory communicatively coupled to the processor where the processor,when operating, being configured to receive a first event reportindicating a first event associated with an electrical distributionsystem, receive a second event report indicating a second eventdifferent from the first event, the second event being associated withthe electrical distribution system, receive a third event reportindicating a third event different from the first event and the secondevent, the third event being associated with the electrical distributionsystem, determine, based upon data associated with the first event andthe second event, that the first event is associated with the secondevent, and to also determine, based upon data associated with the firstevent and the third event, that the first event is not associated withthe third event. The processor, when operating is also configured tocreate a presentation indicating that the first event is related to thesecond event and that the first event is not related to the third event,and provide the presentation to a different process.

In further examples, at least one of the first event report, the secondevent report, or the third event report are able to include a reportindicating at least one of: a status event of a piece of equipment ofthe electrical distribution system, an environmental event, or a powerdistribution system related event. In another example, a group includingthe first event report, the second event report, and the third eventreport includes three unique reports that include a status event of apiece of equipment of the electrical distribution system, anenvironmental event, or a power distribution system related event.

In further examples, the processor is able to also include a userinterface, wherein the processor is further configured to: receive, viathe user interface, a selection of a selected event from within aplurality of events indicated by a respective plurality of eventreports, and define, based on the selection, the selected event as thefirst event.

In further examples, the processor is further configured to: receive afourth event report indicating a fourth event that is different from thefirst event, the second event and the third event, the fourth eventbeing associated with the electrical distribution system, determine,based upon data associated with the first event and data associated withthe fourth event, that the first event is not associated with the fourthevent, determine, based upon data associated with the second event anddata associated with the fourth event, that the second event isassociated with the fourth event. The processor further is configured toassociate the first event with fourth event based upon a combination of:a determination that the first event is associated with the secondevent, and a determination that the second event is associated with thefourth event, wherein the processor is further configured to create thepresentation to further indicate that the first event is related to thefourth event, wherein at least one of the first event report, the secondevent report, the third event report or the fourth event reportcomprises a report with a type indicating at least one of: a statusevent of a piece of equipment of the electrical distribution system, anenvironmental event, or a power distribution system related event, andwherein a type of the second event report is different from a type ofthe fourth event report.

In some examples, the processor is configured to determine the firstevent is associated with the second event is based upon a firstproximity of the first event to the second event, and wherein adetermination that the first event is not associated with the thirdevent is based upon a second proximity of the first event to thirdevent.

In some examples, the first event occurs at a first time and isassociated with a first device, the second event occurs at a second timeand is associated with a second device, and the third event occurs at athird time and is associated with a third device. In such examples, thefirst proximity is based upon a first time difference between the firsttime and the second time, the second proximity is based upon a secondtime difference between the first time and the third time. The processorin such examples is further configured to: determine the first event isassociated with the second event based upon the first time differencebeing below a time threshold; and determine the first event is notassociated with the third event based upon the second time differencebeing above the time threshold; receive a fourth event report indicatinga fourth event associated with a fourth device associated with theelectrical distribution system, the fourth event being different fromthe first event, the second event and the third event; receive a fifthevent report event indicating a fifth event associated with a fifthdevice associated with the electrical distribution system, the fifthevent being different from the first event, the second event, the thirdevent and the fourth event; determine that the first event is associatedwith the fourth event based upon a determination that a distance betweenthe first device and the fourth device is below a distance threshold;determine that the first event is not associated with the fifth event isbased upon a determination that a distance between the first device andthe fifth device is below the a distance threshold. The processor insuch examples is further configured to create the presentation tofurther indicate that the first event is related to the fourth event andis not related to the fifth event.

In some examples, the first event report is sent by a first device, thesecond event report is sent by a second device different from the firstdevice, and the third event report is sent by a third device separatefrom the first device and the second device, wherein the first proximityis based upon a first distance between the first device and the seconddevice, wherein the second proximity is based upon a second distancebetween the first device and the third device. The processor is alsofurther configured to: determine the first event is associated with thesecond event based upon the first distance being below a threshold, anddetermine the first event is not associated with the third event basedupon the second distance being above the threshold. In some examples,the first distance and the second distance are each a respectivedistances according to one or both of electrical power line routings orrespective geographic locations associated with each respective event inthe first event, the second event and the third event.

Further disclosed is a computer program product for determining eventsthat are associated with one another where the computer program productincludes a computer readable storage medium having computer readableprogram code embodied therewith. In an example, the computer readableprogram code comprising instructions for receiving a first event reportindicating a first event associated with an electrical distributionsystem, receiving a second event report indicating a second eventdifferent from the first event, the second event being associated withthe electrical distribution system, receiving a third event reportindicating a third event different from the first event and the secondevent, the third event being associated with the electrical distributionsystem, determining, based upon data associated with the first event andthe second event, that the first event is associated with the secondevent. The computer readable program code also includes instructions fordetermining, based upon data associated with the first event and thethird event, that the first event is not associated with the thirdevent, creating a presentation indicating that the first event isrelated to the second event and that the first event is not related tothe third event, and providing the presentation to a different process.

In an example, the computer readable program code further includeinstructions for: receiving a selection of a selected event from withina plurality of events indicated by a respective plurality of eventreports, and defining, based on the selection, the selected event as thefirst event. In some examples, the first event occurs at a first time,the second event occurs at a second time, and the third event occurs ata third time, wherein the determining the first event is associated withthe second event is based upon a first time difference between the firsttime and the second time. In some examples, determining the first eventis not associated with the third event is based upon a second timedifference between the first time and the third time. In some examples,the instructions for determining the first event is associated with thesecond event determine the first event is associated with the secondevent based upon the first time difference being below a threshold, andthe instructions for determining the first event is not associated withthe third event determine the first event is not associated with thethird event based upon the second time difference being above thethreshold.

In some examples, the first event report is sent by a first device, thesecond event report is sent by a second device different from the firstdevice, and the third event report is sent by a third device separatefrom the first device and the second device, the determining the firstevent is associated with the second event is based upon a first distancebetween the first device and the second device, the determining thefirst event is not associated with the third event is based upon asecond distance between the first device and the third device. In someexamples, the instructions for determining the first event is associatedwith the second event determine the first event is associated with thesecond event based upon the first distance being below a threshold, andthe instructions for determining the first event is not associated withthe third event determine the first event is not associated with thethird event based upon the second distance being above the threshold.

Non-Limiting Examples

Although specific embodiments of the subject matter have been disclosed,those having ordinary skill in the art will understand that changes canbe made to the specific embodiments without departing from the spiritand scope of the disclosed subject matter. The scope of the disclosureis not to be restricted, therefore, to the specific embodiments, and itis intended that the appended claims cover any and all suchapplications, modifications, and embodiments within the scope of thepresent disclosure.

What is claimed is:
 1. A method for determining events that areassociated with one another, the method comprising: receiving a firstevent report indicating a first event associated with an electricaldistribution system; receiving a second event report indicating a secondevent different from the first event, the second event being associatedwith the electrical distribution system; receiving a third event reportindicating a third event different from the first event and the secondevent, the third event being associated with the electrical distributionsystem; determining, based upon data associated with the first event andthe second event, that the first event is associated with the secondevent; determining, based upon data associated with the first event andthe third event, that the first event is not associated with the thirdevent; creating a presentation indicating that the first event isrelated to the second event and that the first event is not related tothe third event; and providing the presentation to a different process.2. The method of claim 1, further comprising: receiving, from a userinterface, a selection of a selected event from within a plurality ofevents indicated by a respective plurality of event reports; anddefining, based on the selection, the selected event as the first event.3. The method of claim 1, wherein at least one of the first eventreport, the second event report, or the third event report comprises areport indicating at least one of: a status event of a piece ofequipment of the electrical distribution system, an environmental event,or a power distribution system related event.
 4. The method of claim 3,wherein at least one of the first event report, the second event report,or the third event report comprises a failure prediction system report.5. The method of claim 1, wherein the determining the first event isassociated with the second event is based upon a first proximity of thefirst event to the second event, and wherein the determining the firstevent is not associated with the third event is based upon a secondproximity of the first event to third event.
 6. The method of claim 5,wherein the first event occurs at a first time, the second event occursat a second time, and the third event occurs at a third time, whereinthe first proximity is based upon a first time difference between thefirst time and the second time, wherein the second proximity is basedupon a second time difference between the first time and the third time,wherein the determining the first event is associated with the secondevent is based upon the first time difference being below a threshold,and wherein the determining the first event is not associated with thethird event is based upon the second time difference being above thethreshold.
 7. The method of claim 5, wherein the first event report issent by a first device, the second event report is sent by a seconddevice different from the first device, and the third event report issent by a third device separate from the first device and the seconddevice, wherein the first proximity is based upon a first distancebetween the first device and the second device, wherein the secondproximity is based upon a second distance between the first device andthe third device, wherein the determining the first event is associatedwith the second event is based upon the first distance being below athreshold, and wherein the determining the first event is not associatedwith the third event is based upon the second distance being above thethreshold.
 8. The method of claim 7, wherein the first distance and thesecond distance are each a respective distance according to one or bothof electrical power line routings or respective geographic locationsassociated with each respective event in the first event, the secondevent and the third event.
 9. A processor, comprising: a processor; amemory communicatively coupled to the processor; the processor, whenoperating, being configured to: receive a first event report indicatinga first event associated with an electrical distribution system; receivea second event report indicating a second event different from the firstevent, the second event being associated with the electricaldistribution system; receive a third event report indicating a thirdevent different from the first event and the second event, the thirdevent being associated with the electrical distribution system;determine, based upon data associated with the first event and thesecond event, that the first event is associated with the second event;determine, based upon data associated with the first event and the thirdevent, that the first event is not associated with the third event;create a presentation indicating that the first event is related to thesecond event and that the first event is not related to the third event;and provide the presentation to a different process.
 10. The processorof claim 9, wherein a group comprising the first event report, thesecond event report, and the third event report comprises three uniquereports from a group comprising: a status event of a piece of equipmentof the electrical distribution system, an environmental event, and apower distribution system related event.
 11. The processor of claim 9,further comprising a user interface, wherein the processor is furtherconfigured to: receive, via the user interface, a selection of aselected event from within a plurality of events indicated by arespective plurality of event reports; and define, based on theselection, the selected event as the first event.
 12. The processor ofclaim 9, wherein the processor is further configured to: receive afourth event report indicating a fourth event that is different from thefirst event, the second event and the third event, the fourth eventbeing associated with the electrical distribution system; determine,based upon data associated with the first event and data associated withthe fourth event, that the first event is not associated with the fourthevent; determine, based upon data associated with the second event anddata associated with the fourth event, that the second event isassociated with the fourth event; and associate the first event withfourth event based upon a combination of: a determination that the firstevent is associated with the second event, and a determination that thesecond event is associated with the fourth event, wherein the processoris further configured to create the presentation to further indicatethat the first event is related to the fourth event, wherein at leastone of the first event report, the second event report, the third eventreport or the fourth event report comprises a report with a typeindicating at least one of: a status event of a piece of equipment ofthe electrical distribution system, an environmental event, or a powerdistribution system related event, and wherein a type of the secondevent report is different from a type of the fourth event report. 13.The processor of claim 9, wherein the processor is configured todetermine the first event is associated with the second event is basedupon a first proximity of the first event to the second event, andwherein a determination that the first event is not associated with thethird event is based upon a second proximity of the first event to thirdevent.
 14. The processor of claim 13, wherein the first event occurs ata first time and is associated with a first device, the second eventoccurs at a second time and is associated with a second device, and thethird event occurs at a third time and is associated with a thirddevice, wherein the first proximity is based upon a first timedifference between the first time and the second time, wherein thesecond proximity is based upon a second time difference between thefirst time and the third time, and wherein the processor is furtherconfigured to: determine the first event is associated with the secondevent based upon the first time difference being below a time threshold;determine the first event is not associated with the third event basedupon the second time difference being above the time threshold; receivea fourth event report indicating a fourth event associated with a fourthdevice associated with the electrical distribution system, the fourthevent being different from the first event, the second event and thethird event; receive a fifth event report event indicating a fifth eventassociated with a fifth device associated with the electricaldistribution system, the fifth event being different from the firstevent, the second event, the third event and the fourth event; determinethat the first event is associated with the fourth event based upon adetermination that a distance between the first device and the fourthdevice is below a distance threshold; and determine that the first eventis not associated with the fifth event is based upon a determinationthat a distance between the first device and the fifth device is belowthe a distance threshold, wherein the processor is further configured tocreate the presentation to further indicate that the first event isrelated to the fourth event and is not related to the fifth event. 15.The processor of claim 13, wherein the first event report is sent by afirst device, the second event report is sent by a second devicedifferent from the first device, and the third event report is sent by athird device separate from the first device and the second device,wherein the first proximity is based upon a first distance between thefirst device and the second device, wherein the second proximity isbased upon a second distance between the first device and the thirddevice, wherein the processor is further configured to: determine thefirst event is associated with the second event based upon the firstdistance being below a threshold, and determine the first event is notassociated with the third event based upon the second distance beingabove the threshold.
 16. The processor of claim 15, wherein the firstdistance and the second distance are each a respective distancesaccording to one or both of electrical power line routings or respectivegeographic locations associated with each respective event in the firstevent, the second event and the third event.
 17. A computer programproduct for determining events that are associated with one another, thecomputer program product comprising: a computer readable storage mediumhaving computer readable program code embodied therewith, the computerreadable program code comprising instructions for: receiving a firstevent report indicating a first event associated with an electricaldistribution system; receiving a second event report indicating a secondevent different from the first event, the second event being associatedwith the electrical distribution system; receiving a third event reportindicating a third event different from the first event and the secondevent, the third event being associated with the electrical distributionsystem; determining, based upon data associated with the first event andthe second event, that the first event is associated with the secondevent; determining, based upon data associated with the first event andthe third event, that the first event is not associated with the thirdevent; creating a presentation indicating that the first event isrelated to the second event and that the first event is not related tothe third event; and providing the presentation to a different process.18. The computer program product of claim 17, the computer readableprogram code further comprising instructions for: receiving a selectionof a selected event from within a plurality of events indicated by arespective plurality of event reports; and defining, based on theselection, the selected event as the first event.
 19. The computerprogram product of claim 18, wherein the first event occurs at a firsttime, the second event occurs at a second time, and the third eventoccurs at a third time, wherein the determining the first event isassociated with the second event is based upon a first time differencebetween the first time and the second time, wherein the determining thefirst event is not associated with the third event is based upon asecond time difference between the first time and the third time,wherein the instructions for determining the first event is associatedwith the second event determine the first event is associated with thesecond event based upon the first time difference being below athreshold, and wherein the instructions for determining the first eventis not associated with the third event determine the first event is notassociated with the third event based upon the second time differencebeing above the threshold.
 20. The computer program product of claim 18,wherein the first event report is sent by a first device, the secondevent report is sent by a second device different from the first device,and the third event report is sent by a third device separate from thefirst device and the second device, wherein the determining the firstevent is associated with the second event is based upon a first distancebetween the first device and the second device, wherein the determiningthe first event is not associated with the third event is based upon asecond distance between the first device and the third device, whereinthe instructions for determining the first event is associated with thesecond event determine the first event is associated with the secondevent based upon the first distance being below a threshold, and whereinthe instructions for determining the first event is not associated withthe third event determine the first event is not associated with thethird event based upon the second distance being above the threshold.